AACFlow против n8n
AACFlow — ИИ-рабочее пространство, где команды создают, развёртывают и сопровождают ИИ-агентов визуально, в диалоге или кодом. Вот как AACFlow соотносится с n8n по архитектуре платформы, возможностям ИИ, интеграциям, ценам, безопасности и поддержке. Каждый факт ниже подтверждён источником и датой, последняя проверка: .
AACFlow — ИИ-рабочее пространство для создания, развёртывания и сопровождения ИИ-агентов. На этой странице AACFlow сравнивается с n8n по архитектуре платформы, возможностям ИИ, интеграциям, ценам, безопасности и соответствию требованиям, наблюдаемости и поддержке; используются факты с источниками и датами для тех, кто выбирает между двумя платформами.
Что такое AACFlow?
AACFlow is the AI workspace where teams build, deploy, and manage AI agents, connecting 1,000+ integrations and every major LLM to automate real work visually, conversationally, or with code.
Что такое n8n?
n8n is a fair-code workflow automation platform combining a visual, node-based builder with custom code and built-in AI/agent nodes, available as a self-hosted or cloud-hosted product.
AACFlow и n8n: сравнение по возможностям
В разделах ниже AACFlow и n8n сравниваются по платформе и развёртыванию, ценам, безопасности и соответствию требованиям, возможностям ИИ, интеграциям, наблюдаемости и поддержке.
Платформа и развёртывание
CompareAACFlow vs n8n
AACFlow
n8n
Тип конструктора
AACFlow
Visual canvas, chat, or code (источник: AACFlow Docs: Introduction (visual, natural-language, and API/SDK building), откроется в новой вкладке)Visual drag-and-drop canvas, natural-language (Chat), or code (API/SDK)
n8n
Visual canvas plus code node and AI builder (источник: n8n AI Workflow Builder docs, откроется в новой вкладке)Hybrid visual/code node-based builder. n8n's core interface is a visual, drag-and-drop node canvas where each node is a step. It supports a Custom Code node (JavaScript/Python) and an HTTP Request Tool for arbitrary API calls, plus a natural-language AI Workflow Builder, gated by pricing tier rather than a beta flag, that generates an editable draft workflow from a text prompt.
Порог входа
AACFlow
Low, plus natural-language Chat for non-technical users (источник: AACFlow Docs: Introduction (visual, natural-language, and API/SDK building), откроется в новой вкладке)Low for visual building; natural-language Chat surface (with a workflow-scoped Copilot) for non-technical builders. Chat lets users describe a workflow in plain language and have AACFlow scaffold or edit it; the visual canvas requires no code to connect blocks.
n8n
No official rating; easy visually, code needs skillUnknown / not vendor-quantified. n8n does not publish a formal learning-curve metric. Node-based visual building is broadly described in docs and tutorials as approachable for non-developers on simple flows, while advanced AI-agent and expression/code usage assumes technical familiarity.
Варианты развёртывания
AACFlow
Managed cloud, no single-tenant VPC option (источник: AACFlow Pricing Page, откроется в новой вкладке)Cloud-hosted (managed, multi-tenant SaaS) operated by AACFlow. No documented managed single-tenant/VPC hosting tier. AACFlow is sold as a managed cloud service; there is no dedicated-instance/VPC offering.
n8n
Cloud, npm, Docker Compose, or Kubernetes Helm (источник: n8n docs: Choose how to use n8n, откроется в новой вкладке)Cloud (n8n-managed) and self-hosted via npm, Docker/Docker Compose, or Kubernetes (official Helm chart). Self-hosting can be run via npm, Docker, or a server. A separate n8n-io/n8n-hosting GitHub repo and Helm chart (oci://ghcr.io/n8n-io/n8n-helm-chart/n8n) provide reference deployments for Docker Compose and Kubernetes, and cloud deployment guides cover AWS, Azure, and GCP.
Шаблоны
AACFlow
(источник: AACFlow codebase: templates gallery and APIs removed, откроется в новой вкладке)No: the pre-built workflow template gallery (landing and in-workspace) was removed platform-wide. AACFlow now surfaces per-integration starter prompts instead of a template library.
n8n
(источник: n8n.io Workflow Templates directory, откроется в новой вкладке)Yes: large public template library (thousands of workflows). n8n.io/workflows is a public directory of community-submitted workflow templates, with roughly 10,000+ templates as of mid-2026 and a dedicated AI-workflow category.
Продвижение между средами
AACFlow
(источник: AACFlow Docs: Workspace Forks, откроется в новой вкладке)Yes: fork a whole workspace into a dev/qa/prod-style child, diff it, and promote or roll back changes in either direction. Credential and env-var remapping is required before every promote, so secrets are never silently copied across environments. Gated to the Enterprise plan.
n8n
(источник: Push and pull changes | Administer | n8n Docs, откроется в новой вкладке)Yes: Git-backed Environments feature promotes whole projects between instances. n8n's 'Source control and environments' feature links an n8n instance/project to a Git repository and branch, and supports pushing a full project's workflows, credential references, and variables from one environment (e.g. development) to Git, then pulling into another (e.g. staging/production). Whole-project promotion, not just single-workflow versioning. Supported topologies include multiple instances on one branch (simple push then pull) or multiple instances on multiple branches (requiring a Git-provider pull request/merge). Instance owners/admins can push and pull; project admins can push but not pull. Credential values and variable values are not synced via Git and must be configured manually per environment. This is an Enterprise-tier feature.
Контроль версий
AACFlow
Deployment rollback plus Copilot edit diff/revert (источник: AACFlow codebase: WorkflowDiffEngine, откроется в новой вкладке)Deployed-version history with rollback for every workflow; server-persisted checkpoint/revert and visual diff (accept/reject) specifically for Copilot AI edits. Manual drag-and-drop undo/redo is client-side/localStorage only (capped at 100 ops, 5 stacks), not server-synced across devices. Deployment history does not include an arbitrary version-to-version diff tool, and knowledge base documents have no version history.
n8n
Version history with restore and compare, no branching (источник: View change history | Build | n8n Docs, откроется в новой вкладке)Server-persisted workflow version history with restore and side-by-side compare; no true branching; undo/redo not a distinct persisted feature. n8n maintains a server-side Workflow History of prior saved versions, each capturing node/parameter changes. Users can restore a workflow to a selected version (n8n auto-saves the current state as a new version before restoring, so restores are themselves reversible), open a version in a new tab to compare it against the current workflow, create a new workflow from a historical version, download a version as JSON, and pin or name a version to exempt it from automatic pruning. Retention is tiered: full history on Enterprise Cloud/Self-hosted, 5 days on Cloud Pro, 24 hours for all other users/plans. Git-based branching exists only at the environment/project level, not as per-workflow Git branches. In-editor undo/redo exists but is not documented as a separately persisted, server-tracked mechanism distinct from workflow history.
Совместная работа в реальном времени
AACFlow
(источник: AACFlow codebase: realtime presence handler (cursor/selection broadcast), откроется в новой вкладке)Yes: live multiplayer editing of the same workflow canvas, with real-time cursors, selection broadcasting, and synced concurrent edits over a dedicated realtime backend
n8n
(источник: Community edition features | n8n Docs, откроется в новой вкладке)No: n8n does not support live concurrent multi-user canvas editing with cursors/selections/synced operations. Collaboration is handled through async workflow sharing, project-based access, and Git-based source control (Enterprise), not real-time co-editing; community edition additionally lacks any workflow sharing at all.. Enterprise adds Git source control and project sharing, but there is no live-cursor or simultaneous canvas editing support.
Встроенное файловое хранилище
AACFlow
(источник: AACFlow codebase: file share modal (password/email/SSO modes), откроется в новой вкладке)Yes: a native Files area with folder hierarchy, link-based sharing (public, password, email OTP, or SSO auth), and a workspace-level Recently Deleted view covering workflows, tables, knowledge bases, files, and folders. Admins can restrict which share-auth modes (public/password/email/SSO) a permission group is allowed to use.
n8n
(источник: How to Set Up n8n's Internal File Storage, откроется в новой вкладке)No: n8n does not have a Drive-like native file storage system with folder hierarchy, link-based sharing (password/SSO), and deleted-item recovery. Its "file storage" is binary data handling scoped to workflow executions (local filesystem/S3-compatible backend config) or per-node file operations, not a user-facing file manager.. n8n docs describe binary data storage mode (filesystem/S3) for execution artifacts and per-node file/folder operations (e.g. Google Drive node), not an internal shared-drive product surface.
Встроенные таблицы данных
AACFlow
(источник: AACFlow Docs: Tables, откроется в новой вкладке)Yes: a native spreadsheet-like Tables feature (typed columns, not an external DB connector) with full keyboard support (arrow keys, Tab, copy-paste bulk load, Cmd/Ctrl+Z undo) and atomic per-row writes from multiple workflows at once. No public fixed row-limit figure is documented (guidance says paginate reads past ~100k rows); a workflow can also be wired to run per row via a "workflow column."
n8n
(источник: Data tables | n8n Docs, откроется в новой вкладке)Yes: n8n has a native Data Table feature (Data Table node, DataTable API, and a Data tables UI tab) for creating and managing structured tables of rows and columns directly inside an n8n instance, without an external database.. Storage is capped at 50MB per instance by default (self-hosted instances can raise this via the N8N_DATA_TABLES_MAX_SIZE_BYTES environment variable); direct programmatic access from a Code node isn't supported. Spreadsheet-style keyboard navigation isn't explicitly documented.
Редактор документов с форматированием
AACFlow
(источник: AACFlow codebase: rich markdown editor, откроется в новой вкладке)Yes: markdown files opened in the Files viewer render in an inline WYSIWYG-style rich markdown editor, with inline @-mention links to other AACFlow resources
n8n
(источник: Sticky Notes | n8n Docs, откроется в новой вкладке)No: n8n does not have a document-oriented WYSIWYG rich-text editor. Its closest analog is Sticky Notes on the workflow canvas, which support Markdown formatting (headers, bold, lists, code blocks, embedded images/YouTube) but are edited as raw Markdown text, not a WYSIWYG editor, and are canvas annotations rather than stored documents.. Sticky notes render Markdown via markdown-it/CommonMark but are edited in plain-text/raw-source mode, not an inline WYSIWYG surface.
Подворкфлоу (композиция)
AACFlow
(источник: AACFlow Docs: Workflow block, откроется в новой вкладке)Yes: a Workflow block calls another saved workflow as a step, waits for it to finish, runs its latest deployed version, and maps parent variables into the child's input form. Self-references are blocked to prevent infinite recursion.
n8n
(источник: Execute Sub-workflow | Nodes | n8n Docs, откроется в новой вкладке)Yes: the Execute Sub-workflow node calls a saved workflow as a step in another workflow, with a 'Wait for Sub-Workflow Completion' option so the parent pauses until the child finishes, passing data in via the child's trigger and receiving data back from the child's last node.. The child workflow starts with a 'When Executed by Another Workflow' trigger that defines the expected input fields. When 'Wait for Sub-Workflow Completion' is enabled, the parent blocks until the sub-workflow finishes and receives whatever data the sub-workflow's final node outputs; disabling it lets the parent continue without waiting.
Собственные блоки (повторное использование в организации)
AACFlow
(источник: AACFlow codebase: custom-blocks publish API (admin gate), откроется в новой вкладке)Yes: a user with admin access on a workflow's workspace can publish its deployed version as a named, iconed custom block that appears in the block toolbar for the whole organization. Inputs are read live from the source workflow's Start block; the publisher picks which outputs to expose. The block always runs the source workflow's latest deployed version, and its internal steps and intermediate values are never exposed to consumers. Enterprise-gated. Distinct from the Workflow (sub-workflow) block, which composes a workflow the same author controls, and from custom code/tool blocks, which run inline code rather than a full deployed workflow.
n8n
(источник: Execute Sub-workflow | Nodes | n8n Docs, откроется в новой вкладке)No: n8n has no feature to publish a deployed workflow as a named, encapsulated block that appears in the node panel for other users to drag into their own separate workflows. The closest built-in mechanism is the Execute Sub-workflow node, which calls another saved workflow (by database lookup, local file, parameter, or URL) from inside a workflow, but it is a generic caller node, not a distinct, iconed, named block per source workflow.. An n8n community feature request, 'Mark workflow as a custom node to be re-used in other workflows' (opened August 2024), asks for exactly this: turning a workflow into a reusable node listed under its own category in the node panel, with defined input parameters, so other builders can add it without touching the source workflow's internals. n8n has not shipped it; the documented mechanism remains the generic Execute Sub-workflow node. n8n's actual node-level encapsulation mechanism, custom/community nodes, requires writing and packaging real TypeScript code as an npm module, not publishing a no-code workflow someone built visually.
Тарифы
CompareAACFlow vs n8n
AACFlow
n8n
Модель ценообразования
AACFlow
Credit-based billing, BYOK exempt from caps (источник: AACFlow Pricing, откроется в новой вкладке)Credit-based usage billing (Stripe), with bring-your-own-key exemption from metered caps
n8n
Billed by monthly workflow executions (источник: n8n Pricing, откроется в новой вкладке)Per-workflow-execution pricing tiers, unlimited users at every tier. n8n's pricing page states workflows are billed by monthly execution count. A workflow that runs start-to-finish counts as one execution regardless of the number of steps or nodes. Unlimited users are included at every paid tier.
Начальный платный тариф
AACFlow
Pro plan at $25/user/month (источник: AACFlow Pricing, откроется в новой вкладке)Pro: $25 per user/month
n8n
€20/month, 2,500 executions (источник: n8n Pricing, откроется в новой вкладке)Starter plan: €20/month (billed annually), 2,500 executions/month, cloud-hosted. Starter includes 2,500 workflow executions per month, 5 concurrent executions, 1 shared project, unlimited users, 2,300 AI credits, and forum support.
Бесплатный уровень
AACFlow
(источник: AACFlow Pricing, откроется в новой вкладке)No free tier: usage is paid for with prepaid wallet credits or a paid plan
n8n
(источник: n8n docs: Choose how to use n8n, откроется в новой вкладке)Yes: free self-hosted Community Edition, plus a free cloud trial (no credit card). The Community Edition is a free, self-hosted version of n8n runnable on a user's own infrastructure. Separately, n8n Cloud offers a free trial of the Starter/Pro plans without requiring a credit card.
Собственный ключ (BYOK)
AACFlow
(источник: AACFlow Docs: Bring Your Own Key (BYOK), откроется в новой вкладке)Yes: bring-your-own-key support exempts usage from metered credit caps, and multiple keys stored for the same provider are automatically round-robin rotated, with automatic fallback past any key that fails to decrypt
n8n
De facto via provider API keys, not named (источник: n8n docs: OpenAI credentials, откроется в новой вкладке)De facto yes: Chat Model nodes require users' own provider API credentials, though n8n does not name this "BYOK". n8n's OpenAI and Anthropic credential docs both walk users through generating an API key in the provider's own console and entering it as the node credential; no n8n-hosted key is supplied for these Chat Model nodes. Separately, n8n's pricing page describes plan-included 'AI credits' (2,300 on Starter, up to 13,700+ on higher tiers) for n8n's own in-app AI Assistant feature, which is distinct from the provider credentials Chat Model nodes require. n8n does not name a bring-your-own-API-key policy, but requiring each provider's own key for Chat Model nodes makes BYOK the de facto default for workflow-level LLM calls.
Безопасность и соответствие требованиям
CompareAACFlow vs n8n
AACFlow
n8n
SOC 2
AACFlow
(источник: AACFlow Landing Page, откроется в новой вкладке)No third-party SOC 2 report is claimed
n8n
Aligned to SOC 2, report on request (источник: n8n Trust Center, откроется в новой вкладке)SOC 2: program 'aligned to' SOC 2 with annual third-party audits; report available to enterprise customers via Trust Center. n8n operates a Trust Center (trust.n8n.io, powered by SafeBase) covering security, compliance, privacy, and reliability. Its security program is aligned to the SOC 2 framework, with continuous evaluation and annual independent audits, and the SOC 2 report is provided to enterprise customers on request rather than published openly.
Резидентность данных
AACFlow
Cloud region toggle is global, not per-customer (источник: AACFlow codebase: async job region resolution, откроется в новой вкладке)On AACFlow Cloud, async job execution has an internal US/EU region toggle, but it is deployment-wide, not a customer-selectable per-workspace residency option
n8n
(источник: n8n docs: Choose how to use n8n, откроется в новой вкладке)Yes: achievable via self-hosting; specific cloud data-residency regions not confirmed. Full self-hosting (Docker, Kubernetes, or npm, on any infrastructure including on-prem) gives complete control over where data lives. n8n Cloud's own selectable data-residency regions are not documented.
Ролевой контроль доступа
AACFlow
(источник: AACFlow Docs: Roles and Permissions, откроется в новой вкладке)Yes: admin/write/read workspace permissions, org-level admin/member roles, plus Enterprise-tier permission groups that allow/deny-list specific models, tools, and integrations per group on top of those base roles. See modelAndToolGovernance and credentialGovernance for the finer-grained permission-groups layer.
n8n
(источник: n8n Blog: Custom Project Roles and SSO provisioning, откроется в новой вкладке)Yes: role-based access control available on all plans except Community edition. RBAC manages access to workflows and credentials via projects and project roles, available on all plans except the free Community edition. Custom Project Roles (granular, admin-definable permissions) is an Enterprise-only feature.
Журнал аудита
AACFlow
(источник: AACFlow codebase: auditLog table, откроется в новой вкладке)Yes: dedicated audit_log table plus workflow execution logs, exposed via a public /v1/audit-logs API (Enterprise plan), plus continuous SIEM/warehouse export to Datadog, S3, GCS, Azure Blob, BigQuery, or Snowflake via a data-drains dispatcher
n8n
(источник: n8n Pricing, откроется в новой вкладке)Yes: audit logging available, primarily an Enterprise-tier feature. n8n's security page states audit log history and historical activity records are kept for at least 12 months, with at least the last three months immediately available for analysis, and collects/centrally stores these logs for authorized users with SIEM export/log streaming. Per the pricing page, unlimited execution log retention and enforced audit logging are listed under the Enterprise tier's feature set.
Дополнительное соответствие требованиям
AACFlow
None claimed (источник: AACFlow Enterprise Page, откроется в новой вкладке)None claimed. No additional third-party certification is claimed.
n8n
GDPR, SOC 2 Type II certified, public SOC 3 report (источник: n8n Trust Center | Powered by SafeBase, откроется в новой вкладке)GDPR (as data processor), SOC 2 Type II certification, and a publicly downloadable SOC 3 report; no HIPAA, ISO 27001, PCI, or FedRAMP certification found. n8n's Trust Center (SafeBase-hosted) and legal/security page list GDPR compliance (as a data processor with a standard DPA), CAIQ self-assessment questionnaires for both cloud and self-hosted deployments, and a SOC 3 report that is publicly downloadable from the Security page. n8n now holds SOC 2 Type II certification, viewable via the Trust Center, in addition to the public SOC 3 report. n8n holds no ISO 27001, HIPAA BAA, PCI-DSS, or FedRAMP certification. Third-party blog posts describe self-hosted n8n as helping organizations map to HIPAA/ISO 27001 requirements, but that is not the same as holding those certifications.
Управление моделями и инструментами
AACFlow
(источник: AACFlow codebase: PermissionGroupConfig (allowedModelProviders, deniedModels, deniedTools), откроется в новой вкладке)Yes: enterprise "permission groups" let an admin allow-list/deny-list specific LLM providers and models, and separately deny specific tools/integrations (or disable all MCP or custom tools) per group, layered on top of workspace admin/write/read roles. This does not control whether an LLM provider retains prompts. AACFlow offers no "zero data retention" mode or governed AI gateway. A separate, Enterprise-gated feature lets orgs set a log-retention window and redact PII, but that only controls how long AACFlow itself keeps execution logs.
n8n
Not publicly documentedUnknown. Not publicly documented by n8n.
Управление учётными данными
AACFlow
(источник: AACFlow Docs: Roles and Permissions, откроется в новой вкладке)Yes: shared credentials (connected accounts, service accounts, workspace secrets) are their own nested permission level (Member/Admin) below organization and workspace roles, and enterprise permission groups can further allow-list specific integrations and restrict which file-share auth modes (public/password/email/SSO) a group may use. A user's personal environment variables/secrets are never shared or inherited by anyone, including org owners/admins.
n8n
(источник: See available roles | Administer | n8n Docs, откроется в новой вкладке)Yes: n8n's RBAC model is project-based, with built-in Admin/Editor/Viewer project roles, and custom project roles (Enterprise feature) let admins scope access across resource types, including credentials, workflows, folders, data tables, variables, and source control, beyond the default three roles.. n8n's docs describe access control as project-based rather than scope-based: users get one of three built-in project roles (Admin, Editor, Viewer). Custom Project Roles (Enterprise) let admins build least-privilege roles whose permission surface spans Projects, Folders, Workflows, Credentials, Data tables, Variables, and Source control, rather than being limited to the three default roles.
Единый вход (SSO)
AACFlow
(источник: AACFlow Docs: Single Sign-On (SSO), откроется в новой вкладке)Yes: SAML 2.0 and OIDC single sign-on, with users routed to SSO by their email domain, plus SCIM 2.0 directory provisioning for Okta, Microsoft Entra ID, OneLogin, and JumpCloud that creates, updates, deactivates, and removes members and maps pushed groups to permission groups, workspace access, and the organization admin role
n8n
(источник: Set up SAML | n8n Docs, откроется в новой вкладке)Yes: n8n supports SAML and OIDC single sign-on on Business/Enterprise plans, including automated user provisioning that assigns a user's instance role and project access from their identity-provider attributes on first login.. Works with Okta, Azure AD, or any SAML-compliant IdP. The role/project mapping is driven by IdP attributes named n8n_instance_role and n8n_projects, and is documented as part of Enterprise governance features.
Настраиваемая политика сессий
AACFlow
(источник: AACFlow Docs: Session Policies, откроется в новой вкладке)Yes: Enterprise organization owners and admins can set a max session lifetime (1 to 8,760 hours from sign-in, regardless of activity) and an idle timeout (48 to 8,760 hours without activity), applied to every member on every device. Both limits are optional; leaving them empty keeps the default of 30-day sessions that extend automatically while a member stays active. A separate "Sign out all members" action immediately revokes every member session in the organization except the admin's own, for use after a security incident or an offboarding wave. The 48-hour idle floor exists because session activity is recorded at most once per day, so a shorter window could sign out members who are actively working.
n8n
Self-hosted JWT duration env vars, no Cloud setting (источник: User management and 2FA | Deploy | n8n Docs, откроется в новой вкладке)Partial: self-hosted only and env-var driven. N8N_USER_MANAGEMENT_JWT_DURATION_HOURS sets how long a signed-in session JWT lasts (default 168 hours, one week) and N8N_USER_MANAGEMENT_JWT_REFRESH_TIMEOUT_HOURS controls sliding refresh, where 0 means refresh at 25% of the duration and -1 disables refresh so the duration becomes a hard re-login deadline.. Both are instance-level environment variables set at deploy time rather than an admin console setting, and fractional values (for example 0.5 for 30 minutes) are accepted. The pair was added in n8n 1.26.0 in response to a community request for a session-time limit. Configuring them requires control of the host, so they are not available to n8n Cloud customers, and n8n does not document a Cloud- or Enterprise-tier session-lifetime setting; SAML/OIDC SSO on Business/Enterprise plans handles authentication but n8n does not document inheriting an IdP session lifetime.
Проверенные собственные интеграции
AACFlow
(источник: AACFlow codebase: first-party block directory, откроется в новой вкладке)Yes: every one of AACFlow's 266 blocks is first-party authored and code-reviewed through the standard pull-request process in the main AACFlow repository; there is no public marketplace where an arbitrary third party can publish and have other users install executable tool code without going through AACFlow's own review. Custom code steps run inside AACFlow's own isolated-vm sandbox rather than as an installable third-party skill package, so the supply-chain trust boundary is AACFlow's codebase review, not an open registry.
n8n
First-party nodes plus an open, lightly-vetted npm community marketplace (источник: Risks when using community nodes | n8n Docs, откроется в новой вкладке)Partial: n8n ships built-in first-party nodes plus an open community-node ecosystem published to public npm, where only a subset carry an official "verified" review. Beyond its built-in nodes, n8n lets any developer publish a community node as a public npm package that other users install by name; only nodes n8n manually reviews for quality and security (and which forgo runtime dependencies) earn the verified shield icon and are installable/discoverable from n8n Cloud, while unverified community nodes can still be installed on self-hosted instances (or disabled via N8N_COMMUNITY_PACKAGES_ENABLED). n8n's docs warn that community nodes run with the same level of access as n8n itself, including decrypted credentials during execution. In January 2026, researchers documented a supply-chain attack in which malicious npm packages posing as n8n community nodes (one mimicking a Google Ads integration) stole OAuth tokens from the credential store; the primary malicious package had 4,241 downloads listed before removal.
Скрытие персональных данных
AACFlow
(источник: AACFlow Docs: Guardrails Block, откроется в новой вкладке)Yes: a Guardrails workflow block detects and blocks or masks PII (30+ entity types across the US, UK, and several other countries) via Microsoft Presidio, in addition to the org-level data-retention PII policy applied to stored data
n8n
(источник: Scrub PII from execution log (feature request, n8n Community), откроется в новой вкладке)No: n8n has no built-in, native PII detection/redaction feature. PII masking is achieved only via community-built nodes or user-assembled workflows (regex/AI-based detection, tokenization) placed before an LLM call; a community feature request to scrub PII from execution logs remains open/unimplemented.. Execution log saving is documented as all-or-nothing today; a community request to add PII/secret scrubbing to logs is still open.
Настраиваемое хранение данных
AACFlow
(источник: AACFlow Docs: Data Retention, откроется в новой вкладке)Yes: Enterprise orgs can independently configure log retention, soft-deletion cleanup, and Chat/Copilot task cleanup (chats, runs, checkpoints, Inbox tasks) at 1 day to 5 years or Forever, applied org-wide with no per-workspace override
n8n
(источник: Manage execution data | Deploy | n8n Docs, откроется в новой вкладке)Yes: n8n lets self-hosted instances configure execution-data retention via environment variables (EXECUTIONS_DATA_MAX_AGE, EXECUTIONS_DATA_PRUNE_MAX_COUNT), and n8n Cloud Enterprise plans support up to 50,000 executions with unlimited retention versus fixed limits on lower tiers.. Default self-hosted retention is 336 hours (14 days) or 10,000 executions, both adjustable; Cloud tiers vary retention window by plan.
White-label (собственный бренд)
AACFlow
(источник: AACFlow Docs: Whitelabeling, откроется в новой вкладке)Yes: Enterprise orgs can replace the logo, wordmark, brand name, and primary/accent theme colors across the workspace UI with their own
n8n
(источник: OEM | Embedded IPaaS | n8n, откроется в новой вкладке)No: n8n's OEM/embed documentation states n8n branding stays visible in the editor when embedded, and full white-labeling is not supported through their OEM offering; only self-hosted customers doing manual source-code modification (editing design-system CSS/Vue components and i18n text) can rebrand it themselves.. n8n's docs say: "If full white-labeling is a hard requirement for your product, OEM isn't the right fit." A full rebrand is only possible via unsupported self-hosted source modification.
Возможности ИИ
CompareAACFlow vs n8n
AACFlow
n8n
Поддержка нескольких LLM
AACFlow
21 providers plus dynamic-resolution aggregators (OpenRouter, LiteLLM, etc.) (источник: AACFlow codebase: PROVIDER_DEFINITIONS, откроется в новой вкладке)21 provider integrations (OpenAI, Anthropic, Google/Gemini, Azure OpenAI, Azure Anthropic, Groq, Cerebras, Mistral, xAI, Bedrock, Vertex, Ollama, OpenRouter, and more), with OpenRouter, LiteLLM, vLLM, and Ollama resolving models dynamically at runtime rather than from a fixed list, so effective model reach extends well beyond the 21 named providers. apps/sim/providers/models.ts defines 21 provider entries.
n8n
(источник: OpenAI Chat Model node docs, откроется в новой вкладке)Yes: many providers via dedicated Chat Model nodes. Documented first-party Chat Model nodes include OpenAI, Anthropic (Claude), Google Gemini, Google Vertex, Azure OpenAI, AWS Bedrock, Mistral Cloud, Cohere, DeepSeek, Groq, xAI Grok, OpenRouter, Ollama (local models), Alibaba Cloud, MiniMax, Moonshot Kimi, NVIDIA Nemotron, Vercel AI Gateway, and Lemonade.
Блоки рассуждений агента
AACFlow
(источник: AACFlow codebase: block registry, откроется в новой вкладке)Yes: dedicated agent, function-calling, RAG, code-execution, and evaluation blocks, not just data routing
n8n
(источник: n8n Tools Agent docs, откроется в новой вкладке)Yes: dedicated AI Agent / Tools Agent node distinct from plain data-routing nodes. The AI Agent node (implemented as a "Tools Agent" since v1.82.0) is an autonomous decision-making node: based on the LLM's reasoning, it selects and calls tools such as other n8n workflows, the Custom Code tool, the HTTP Request tool, MCP tools, or a vector store used as a tool. This is distinct from n8n's standard, deterministic data-transform/routing nodes.
Создание на естественном языке
AACFlow
(источник: AACFlow Docs: Copilot, откроется в новой вкладке)Yes: Chat + in-editor AI Copilot can build and modify workflows from natural-language requests
n8n
(источник: n8n Blog: AI Workflow Builder Best Practices, откроется в новой вкладке)Yes: AI Workflow Builder, generally available on Starter, Pro, and Enterprise Cloud. Users describe a workflow in plain text and the AI Workflow Builder generates a draft, editable node-based workflow with iterative multi-turn refinement. Launched in beta in late 2025, it reached general availability for n8n Cloud customers on the Starter, Pro, and Enterprise plans; self-hosted availability is not documented.
База знаний / RAG
AACFlow
(источник: AACFlow codebase: KB schema (pgvector + tsvector), откроется в новой вкладке)Yes: hybrid vector (pgvector) plus full-text (tsvector) search knowledge base, 11 supported file formats (csv, doc, docx, html, json, md, pdf, pptx, txt, xlsx, yaml), configurable chunking, plus 51 connectors that continuously sync external sources (Google Drive, Confluence, Slack, Gmail, GitHub, HubSpot, Linear, Jira, and more) into the knowledge base rather than a one-shot upload
n8n
(источник: n8n docs: RAG in n8n, откроется в новой вкладке)Yes: native RAG pipeline with multiple vector-store integrations. n8n documents a full RAG pipeline (document loaders, Text Splitter, Embeddings node, Vector Store node) with supported vector stores including Pinecone, Qdrant, Supabase Vector Store, PGVector (Postgres), and an in-memory vector store for testing; vector stores can be retrieved as a tool for an AI Agent.
Поддержка MCP
AACFlow
(источник: AACFlow Docs: Using MCP Tools, откроется в новой вкладке)Yes: both MCP client (call external MCP servers) and MCP server (expose AACFlow workflows as MCP tools)
n8n
(источник: MCP Client Tool docs, откроется в новой вкладке)Yes: native MCP Client Tool and MCP Server Trigger nodes. First-party nodes let an n8n AI Agent call tools exposed by an external MCP server (MCP Client Tool, SSE + JSON-RPC, Bearer/header/OAuth2 auth) and let n8n expose its own workflows as MCP tools to external AI agents (MCP Server Trigger).
Оценка и ограничители
AACFlow
LLM-judge Evaluator plus Guardrails validation block (источник: AACFlow Docs: Evaluator Block, откроется в новой вкладке)Evaluator block (LLM-judge scoring against user-defined named metrics) and Guardrails block (JSON validity, regex, RAG/hallucination scoring, PII detection/masking). These are per-call scoring/validation primitives, not a batch golden-dataset eval-suite runner or A/B prompt-testing harness.
n8n
(источник: n8n Evaluations docs, откроется в новой вкладке)Yes: dedicated Evaluations feature (Light + Metric-based). n8n provides an Evaluation node/trigger and an Evaluations tab supporting 'Light evaluations' (manual test cases during development) and 'Metric-based evaluations' (scoring at scale for production), with built-in metrics (AI-judged Helpfulness, string similarity, categorization, tools-used) plus custom metrics.
Участие человека (human-in-the-loop)
AACFlow
(источник: AACFlow Docs: Human in the Loop Block, откроется в новой вкладке)Yes: dedicated approval block that pauses a run and waits for a human-submitted "Resume Form," with durable pause/resume via persisted execution snapshots and notification hooks (e.g. Slack, email) carrying the resume link
n8n
(источник: Human-in-the-loop for AI tool calls | n8n Docs, откроется в новой вкладке)Yes: dedicated Human-in-the-Loop node built on Wait. n8n has a dedicated Human-in-the-Loop node (a higher-level abstraction built on the underlying Wait node) that pauses an active workflow mid-run and waits on human approval or input, distinct from a plain delay. The approver is notified via a configurable channel, Gmail, Slack, Telegram, Discord, Microsoft Teams, WhatsApp, or n8n's built-in Chat, with 'Approve Only' or 'Approve and Disapprove' options. The run resumes when the reviewer responds via a button or webhook callback, and an optional timeout triggers a fallback path if no response arrives within the configured window (minutes up to a day).
Генеративные медиа
AACFlow
(источник: AACFlow codebase: Image Generator V2, откроется в новой вкладке)Yes: dedicated image (3 provider families incl. OpenAI, Gemini, Fal.ai proxy), video (5 provider families incl. Runway, Veo, Luma, Hailuo, Fal.ai proxy), text-to-speech (7 providers), and speech-to-text (5 providers) blocks
n8n
Via OpenAI/MiniMax nodes, no dedicated nodes (источник: OpenAI Audio operations | n8n Docs, откроется в новой вкладке)Partial: via AI/LLM provider nodes, not dedicated media-gen nodes. No standalone image-generation or video-generation core node family exists. Image, video, TTS, and STT are reached by calling LLM provider nodes inside the LangChain-based AI nodes: the OpenAI node's Image and Audio operations (image generation via DALL-E/gpt-image, TTS, and transcription/translation via Whisper), and the MiniMax node (image generation, video generation from text or a first-frame image, and text-to-speech). Broader coverage such as text-to-3D, faceswap, or upscaling exists only via unofficial community nodes like PiAPI, not built by n8n itself.
Динамическое использование инструментов
AACFlow
(источник: AACFlow codebase: agent tool resolution (pre-wired only), откроется в новой вкладке)No: an Agent block calls tools the workflow author explicitly added to it at build time, rather than browsing and picking from a broader pool (e.g. an entire MCP server catalog) at inference time. Runtime MCP "discovery" exists to resolve/refresh the schema of an already-configured tool. The model does not browse or choose from the server's full tool list.
n8n
Not publicly documentedUnknown. Not publicly documented by n8n.
Автоматическая замена модели
AACFlow
(источник: AACFlow codebase: executeProviderRequest (no retry/fallback), откроется в новой вкладке)No: a failed or rate-limited LLM call is retried using AACFlow's own hosted API keys for the same model, rather than automatically switching to a different model or provider. A "fallback" comment in the provider layer refers to rotating among AACFlow's own hosted API keys for the same model, not switching models.
n8n
Not publicly documentedUnknown. Not publicly documented by n8n.
Навыки агентов
AACFlow
(источник: AACFlow Docs: Agent skills, откроется в новой вкладке)Yes: named, reusable "Agent Skills" (built on the open Agent Skills / SKILL.md format) that agents load on demand via progressive disclosure, editable in-app or imported from a SKILL.md file or GitHub URL. Only the skill name and description sit in the agent's system prompt (~50-100 tokens each); the full instructions load into context only when the agent calls load_skill.
n8n
(источник: Tutorial: Build an AI workflow in n8n, откроется в новой вкладке)No: n8n has no first-class, named reusable prompt/knowledge-snippet object that agents reference. Reuse is achieved informally by exporting/importing workflow JSON or calling a sub-workflow (e.g. a "Tool (Workflow)" node) as a reusable scratchpad, not by a dedicated skills library.. System prompts are configured per AI Agent node; the closest analog is reusable sub-workflows or exported JSON, not a named, invokable skill library.
Встроенное развёртывание чата
AACFlow
(источник: AACFlow Docs: Chat Deployment, откроется в новой вкладке)Yes: a workflow can be deployed as a public, shareable Chat interface with selectable auth (public, password, email OTP, or SSO), in addition to API and MCP deployment targets
n8n
(источник: Chat Trigger | n8n Docs, откроется в новой вкладке)Yes: n8n's Chat Trigger node provides a fully styled, publicly deployable chat window that connects to an AI Agent node, with a configurable public URL, CORS allowed-origins, and streaming responses; Chat Hub additionally offers a centralized multi-model chat interface with a restricted "Chat user" role.. Distinct from form/webhook/API deployment; supports streaming and a dedicated non-builder chat-user role via Chat Hub.
Параллельное выполнение
AACFlow
(источник: AACFlow Docs: Parallel block, откроется в новой вкладке)Yes: a native Parallel block fans a run out into concurrent branches (fixed count or one per list item) and joins their results back into the workflow automatically. Contained blocks run concurrently instead of sequentially, either a fixed number of times or once per item in a list/collection, and each branch's output aggregates for downstream blocks.
n8n
(источник: Execution order in multi-branch workflows | n8n Docs, откроется в новой вкладке)No: in the current (v1) execution order, n8n executes each branch in turn, completing one before starting another, rather than running them concurrently.. n8n does offer a Merge node to recombine split branches, and community workaround patterns exist (e.g. triggering sub-workflows asynchronously and waiting for all to finish), but no native fan-out/fan-in node runs branches concurrently.
Протокол Agent2Agent (A2A)
AACFlow
(источник: AACFlow Docs: A2A integration, откроется в новой вкладке)Yes: a dedicated A2A block sends messages to, tracks and cancels tasks on, and discovers the capabilities of any Agent2Agent (A2A)-compliant external agent via its Agent Card
n8n
(источник: Agent-to-Agent (A2A) Protocol: Implementation and Trade-offs (n8n Blog), откроется в новой вкладке)No: A2A protocol support comes from a community-published node, not a built-in feature of the core product.. Teams experimenting with A2A rely on a community-published node for protocol-level communication; no first-party A2A node ships in n8n core.
Блок цикла / итерации
AACFlow
(источник: AACFlow Docs: Loop block, откроется в новой вкладке)Yes: a Loop container block runs the blocks inside it repeatedly (For a fixed count, ForEach over a collection, While a condition holds, or Do-While), running iterations one after another; concurrent fan-out is a separate Parallel block
n8n
(источник: Loop Over Items (Split in Batches) | Nodes | n8n Docs, откроется в новой вкладке)Yes: the Loop Over Items (Split in Batches) node iterates a list in fixed-size batches, running each batch sequentially through a 'loop' output and combining results through a 'done' output once all batches complete.. Loop Over Items processes a configurable batch size per iteration and re-enters the loop until every input item has passed through, rather than fanning items out concurrently. n8n's docs note this is the primary built-in mechanism for iterative processing, distinct from the Parallel-style concurrent fan-out other flow-logic nodes provide.
Интеграции
CompareAACFlow vs n8n
AACFlow
n8n
Интеграции
AACFlow
1,000+ integrations (266 blocks, ~3,900 tool actions) (источник: AACFlow codebase: BLOCK_REGISTRY, откроется в новой вкладке)1,000+ integrations counting individual API actions, built from 266 first-party blocks and roughly 3,900 underlying tool actions. AACFlow's landing page cites the "1,000+ integrations" figure; the block/tool-action counts are the same integration surface measured at a different level of granularity.
n8n
1,936 listed integrations (источник: n8n.io Integrations directory, откроется в новой вкладке)1,936 integrations (per n8n.io/integrations). The n8n.io integrations directory page lists 1,936 integrations. n8n's GitHub repo description separately advertises a rounder '400+ integrations,' so the two vendor sources disagree slightly.
Типы триггеров
AACFlow
Webhook, cron, chat, REST API, 61 app triggers, plus a diff-aware Tables trigger (источник: AACFlow Docs: Triggers overview, откроется в новой вкладке)Webhook, schedule/cron, chat, REST API, and event-based triggers for 61 apps (Slack, Gmail, GitHub, Stripe, etc.), plus a native row-level trigger on AACFlow Tables that fires on insert/update with an optional column watch-list and emits a before/after diff
n8n
Webhook, cron, chat, MCP, app-specific events (источник: n8n Evaluation Trigger node docs, откроется в новой вкладке)Webhook, schedule/cron, chat, manual, MCP server, evaluation, and app-specific event triggers. n8n has dedicated trigger node types including a generic Webhook trigger, Schedule/Cron trigger, Chat trigger, Manual trigger, Evaluation trigger, MCP Server trigger (exposing workflows as MCP tools), and hundreds of app-specific triggers (e.g. Gmail, Slack, Google Sheets) that fire on native platform events.
Шаги с собственным кодом
AACFlow
(источник: AACFlow Docs: Function block, откроется в новой вкладке)Yes: code-execution block for custom logic
n8n
(источник: Code node docs, откроется в новой вкладке)Yes: JavaScript and Python via Code node, plus a Custom Code Tool for AI agents. n8n's Code node supports both JavaScript and Python for custom logic inside a workflow. A separate Custom Code Tool node lets an AI Agent call arbitrary code as one of its tools.
Настраиваемые песочницы для кода
AACFlow
(источник: AACFlow Docs: Function block - Sandboxes, откроется в новой вкладке)Yes: named sandboxes a workspace maintains and a Function block selects, each declaring a language, its pip or npm dependencies, optional Debian/APT system packages, and optional managed CLI tools from a catalog grouped by cloud, Kubernetes, infrastructure, deployment, data and storage, and security tools; on aacflow.io they require an active Max or Enterprise plan. Only workspace admins can create or edit sandboxes, in Settings → Sandboxes. On aacflow.io each specification is prebuilt into a reusable image so runs pay no install cost. Two sandboxes with the same language, dependency list, system packages, and managed CLI tools share one build. Every managed CLI entry uses a pinned, integrity-checked vendor artifact. With no sandbox selected, remote code runs on the dedicated Function base; import-free JavaScript stays in the local isolated runtime and ignores the sandbox selection either way.
n8n
Self-hosted env-var allowlist; Cloud is a fixed image (источник: Enable modules in Code node | Deploy | n8n Docs, откроется в новой вкладке)Partial: self-hosted only. On a self-hosted instance an admin sets NODE_FUNCTION_ALLOW_BUILTIN to allowlist Node.js built-in modules (by name, or '*' for all) and NODE_FUNCTION_ALLOW_EXTERNAL to allowlist npm packages by name, with those packages sourced from the instance's n8n/node_modules directory; on n8n Cloud the Code node can't import external npm modules, and n8n makes only the crypto built-in and the moment package available.. The two allowlist variables are instance-level environment variables, not per-workflow settings, and when the instance runs task runners they must be set on the runners rather than the main n8n process. n8n's docs describe the '*' wildcard for the built-in allowlist; the external allowlist is documented as specific module names. Python follows the same host-level pattern: n8n v2 removes the Pyodide-based Python Code node in favour of a native-Python task-runner implementation, and the task-runner variables N8N_RUNNERS_STDLIB_ALLOW and N8N_RUNNERS_EXTERNAL_ALLOW allowlist Python standard-library and third-party modules respectively, so the available Python environment is likewise a property of the host deployment rather than a per-workflow setting. There is no per-code-step declaration of packages, OS packages, or preinstalled CLI binaries; changing the dependency set means changing the host instance.
Развёртывание через API
AACFlow
(источник: AACFlow Docs: API Reference - Getting Started, откроется в новой вкладке)Yes: a public REST API (mostly under /api/, with /api/v1 reserved for logs and audit-log endpoints) supporting API-triggered workflow execution and deployment rollback. The API reference does not document SSE streaming, a resumable event buffer, a dedicated API-trigger block, or a chat-deployment surface as part of the REST API itself.
n8n
(источник: Webhook trigger docs, откроется в новой вкладке)Yes: workflows can be triggered/exposed via Webhook trigger as a REST-style endpoint, and via MCP Server Trigger as MCP tools. A workflow's Webhook trigger node gives it a callable HTTP endpoint that functions as a REST API surface for that workflow. Separately, the MCP Server Trigger node lets a workflow (or its component tools) be published for external AI agents to call over MCP. No distinct SDK-generation feature is documented.
SDK и расширяемость
AACFlow
Official Python and TypeScript SDKs, plus MCP, code block, and A2A protocol (источник: AACFlow Docs: Python SDK, откроется в новой вкладке)Official client SDKs exist for Python (aacflow-sdk, pip install aacflow-sdk) and TypeScript/JavaScript (aacflow-sdk, npm install aacflow-sdk), both wrapping the REST API (x-api-key header) with methods like execute_workflow / executeWorkflow, retry-with-backoff, and usage-limit lookups. Extensibility is further extended by MCP (client + server), a sandboxed code-execution block (JS/Python), custom tools, and an Agent-to-Agent (A2A) protocol block for external agent interop
n8n
(источник: n8n API | Connect | n8n Docs, откроется в новой вкладке)No broad multi-language official SDK; extensibility is via the public REST API, the official n8n CLI, and a node-development toolkit. There is no first-party Python/Go/Java client. Instead, extensibility centers on four things: an official TypeScript package (@n8n/rest-api-client) that wraps n8n's public REST API; an n8n CLI for scripting, CI/CD, or agent use; a node-development kit (the n8n-node CLI plus scaffolding and code-standards docs) for building custom or community nodes in TypeScript, with an official verification program for submission; and a large community-nodes ecosystem, installable per self-hosted instance, alongside 400+ built-in integrations.
Публикация как MCP-сервер
AACFlow
(источник: AACFlow Docs: MCP Deployment, откроется в новой вкладке)Yes: any deployed workflow can be published as a tool on an MCP server (private, API-key protected, or public/no-auth), with ready-to-paste client config generated for Codex, Cursor, Claude Code, Claude Desktop, and VS Code
n8n
(источник: MCP Server Trigger | n8n Docs, откроется в новой вкладке)Yes: n8n has an MCP Server Trigger node that turns a workflow into a callable MCP server, exposing a stable production URL that external MCP clients can call to list and invoke the workflow's connected tool nodes (SSE and streamable HTTP supported).. n8n also offers an instance-level MCP server that lets an AI client create/validate/publish whole workflows, in addition to the per-workflow MCP Server Trigger.
Наблюдаемость и надёжность
CompareAACFlow vs n8n
AACFlow
n8n
Трассировка и наблюдаемость
AACFlow
(источник: AACFlow codebase: TraceSpan tree builder, откроется в новой вкладке)Yes: execution logs include a per-block/per-span trace view (duration, cost, token counts, and latency stats like TTFT/TPS) with expandable nested iteration groups, plus a "View Snapshot" frozen copy of the workflow structure and block states at run time for debugging. This trace view is built directly into AACFlow rather than a raw export browsable in an external tool like Jaeger, and does not expose aggregate latency-percentile charts (p50/p95/p99). The run snapshot serves as a log-detail/debugging artifact rather than a resumable mid-run checkpoint.
n8n
Dashboard metrics, not span-level tracing (источник: Insights | n8n Docs, откроется в новой вкладке)Customer-facing Insights dashboard with per-workflow/per-node metrics, not span-level distributed tracing. n8n ships a native, customer-facing 'Insights' dashboard (Pro, Business, and Enterprise plans) showing per-workflow tables of total production executions, failed executions, failure rate, time saved, and time-series trends including P95 execution duration, workflow error rate, and node error rate. This is dashboard/metrics-level observability, not fine-grained span/trace-level tracing of internal node execution. That requires exporting to external tools like OpenTelemetry, SigNoz, or Grafana, which n8n supports feeding but doesn't natively render as spans.
Надёжность и повторные попытки
AACFlow
Tool-call retries (up to 10x); single-attempt job orchestration (источник: AACFlow codebase: ToolRetryConfig (exponential backoff), откроется в новой вкладке)Individual tool/API calls have configurable exponential-backoff retry (up to 10 attempts). The background job-orchestration layer itself retries only once by design. Durability instead comes from consecutive-failure tracking on schedules and the human-in-the-loop snapshot pause/resume mechanism. AACFlow does not offer guaranteed-once-only block execution, a failed-run holding queue for manual recovery, or a "replay a past execution with its original inputs" feature. The per-execution debugging snapshot serves as a log-detail artifact rather than a resumable mid-run checkpoint.
n8n
Per-node retry and manual replay, no checkpointing (источник: Error handling | n8n Docs, откроется в новой вкладке)Per-node retry-on-fail, workflow-level error workflow fallback, and manual/debug replay of past executions with original data; no automatic mid-run checkpoint/resume. Each node can be configured with 'Retry on Fail' (a configurable retry count and wait time between retries). Workflows can also define an Error Workflow, triggered by an Error Trigger node, that runs automatically on failure. For replay, n8n stores past execution data and offers 'Retry with original workflow' (re-runs using the original input data and workflow version from that run) or 'Retry with currently saved workflow' (re-runs that data against the current, edited workflow). Executions can also be opened via 'Debug in editor' to pin prior input data into the canvas. All of this is retry and replay from stored execution data, not automatic mid-workflow checkpointing that resumes from an arbitrary internal breakpoint after a crash.
Оповещения о сбоях
AACFlow
(источник: AACFlow Docs: AACFlow Workspace Events trigger, откроется в новой вкладке)Yes: a sim_workspace_event trigger fires on run success/failure, deployments, and cost/latency spikes, wired to any notification block (Slack, email, webhook) for real-time alerting
n8n
(источник: Error handling | n8n Docs, откроется в новой вкладке)Yes: proactive push notifications via an Error Workflow, not just execution-log lookup. Every workflow can be configured (in Workflow Settings) with a designated Error Workflow, which must start with an Error Trigger node. This fires automatically whenever the parent workflow's execution fails, and the Error Workflow can then push notifications through any channel node (Slack, email/Gmail, Teams, etc.) carrying the execution ID, workflow name, error message, and stack trace. This is proactive push alerting, distinct from passively browsing the executions list. N8n does not natively define cost- or latency-threshold alerting as a first-class feature; the Insights dashboard's P95 duration is queryable, not push-alerted, though teams can build threshold alerting on top via the Error Workflow/API plus external monitoring.
Выгрузка данных (data drains)
AACFlow
(источник: AACFlow Docs: Data Drains, откроется в новой вкладке)Yes: Enterprise orgs can continuously export workflow logs, job logs, or audit logs on a schedule to a customer-owned S3 bucket, GCS bucket, Azure Blob container, BigQuery table, Snowflake table, Datadog logs intake, or an HTTPS webhook. Each drain exports exactly one data source; multiple drains are created to export multiple sources. Viewing drain config/run history is restricted to org owners/admins.
n8n
(источник: Log streaming | n8n Docs, откроется в новой вкладке)Yes: n8n Enterprise plans include Log Streaming, which continuously sends workflow and audit events (n8n.workflow, n8n.audit, etc.) to external destinations configured as webhook, syslog, or Sentry.. No native built-in S3/BigQuery/Datadog connector type is documented; webhook/syslog/Sentry are the three destination types, with webhook usable to relay onward.
Асинхронное выполнение
AACFlow
(источник: AACFlow codebase: async execution handler, откроется в новой вкладке)Yes: a workflow can be triggered in fire-and-forget async mode, returning HTTP 202 with an execution ID immediately, then polled through the canonical execution resource across queued/running/terminal states. Async runs are tracked by execution ID through the same execution status endpoint used for durable logs rather than a separate queue-job resource.
n8n
(источник: n8n Docs: Webhook node (Respond options, incl. "Immediately"), откроется в новой вкладке)Yes: n8n supports async execution. The Webhook node's "Respond" setting can be set to "Immediately," which sends back an HTTP response (with the message "Workflow got started") right away while the workflow keeps running in the background; n8n's Wait node can also pause a running execution (persisting its state to the database) and resume later on a time interval or an incoming webhook call.. This is a workflow-level pattern (respond-then-continue, or pause-and-resume), not a single unified async job-polling API documented as a first-class feature; callers needing a result must build their own callback or a second polling endpoint.
Лимиты выполнения
AACFlow
5-50 min sync; async defaults to 90 min, Enterprise up to 7 days (источник: AACFlow Docs: Concurrent Executions, откроется в новой вкладке)Plan-gated: synchronous runs time out at 5 minutes on accounts without a plan and 50 minutes on paid plans; async runs default to 90 minutes, while Enterprise policy can be configured up to 7 days; concurrency ranges from 10 to 1,000 executions per billing account depending on plan. A direct async API request can shorten the account policy for that request, but cannot extend it. Concurrency limits are published in the platform cost docs, where the Enterprise limit is 1,000 by default and customizable. A run that exceeds its time limit is terminated and marked failed with a timeout error.
n8n
Configurable timeout (max 3600s) and concurrency limits (источник: n8n Docs: Executions environment variables (EXECUTIONS_TIMEOUT, EXECUTIONS_TIMEOUT_MAX), откроется в новой вкладке)n8n publishes concrete configurable limits: EXECUTIONS_TIMEOUT (default -1, disabled) sets a default per-workflow timeout in seconds and EXECUTIONS_TIMEOUT_MAX (default 3600 seconds, i.e. 1 hour) caps how long any individual workflow's timeout override can be set to; concurrency is capped by N8N_CONCURRENCY_PRODUCTION_LIMIT for production (webhook/trigger-started) executions, with excess runs queued and processed FIFO once capacity frees up. In queue mode, each worker's parallel job count is configurable via a --concurrency flag.. These are self-hosted environment-variable defaults from n8n's own docs; n8n Cloud plans may impose their own separate execution/concurrency caps, which are not published. The worker --concurrency flag's default value is also not documented.
Обработка частичных сбоев
AACFlow
(источник: AACFlow codebase: error-output edge routing, откроется в новой вкладке)Yes: any block can be wired to a dedicated error-output edge, so a failing step routes execution down an error-handling branch instead of always halting the entire run
n8n
(источник: n8n Docs: Work with nodes (On Error: Stop Workflow / Continue / Continue Using Error Output), откроется в новой вкладке)Yes: n8n lets you set a per-node "On Error" behavior of "Continue (using error output)," which routes that node's error down a separate error output branch while the rest of the workflow keeps running, in addition to "Continue" (proceed using last valid data) and "Stop Workflow" (halt entirely); separately, an entire workflow can have a designated Error Workflow (built from an Error Trigger node) that fires when the main workflow fails, for alerting/cleanup.. Community bug reports (e.g. on the Sort and HTTP Request nodes) show the error-output routing does not always behave consistently across every node type.
Выполнение без присмотра
AACFlow
(источник: AACFlow codebase: trigger.dev background job backend, откроется в новой вкладке)Yes: scheduled, webhook, and chat-triggered runs execute as background jobs on trigger.dev workers, entirely on AACFlow's servers. No client device needs to be open, awake, or connected for a run to fire or complete; closing the browser tab or shutting down a laptop has no effect on a scheduled or triggered workflow.
n8n
(источник: n8n Community: Does the process continue if I close the browser window?, откроется в новой вкладке)Yes: active trigger-based executions (schedule, webhook, etc.) keep running on the n8n instance itself after a user closes their browser, whether that instance is n8n Cloud or a self-hosted server. n8n staff confirm in the community forum that once a workflow is activated with a trigger, execution continues on the n8n instance independent of the browser tab that was used to activate it; only workflows kicked off via a manual 'Execute Workflow' click stop when the browser closes mid-run. Since n8n itself is a server process (n8n Cloud or a self-hosted Docker/Kubernetes/host-machine instance) rather than a desktop app, unattended trigger-based runs depend on that server staying up, not on any individual client device.
Поддержка
CompareAACFlow vs n8n
AACFlow
n8n
Каналы поддержки
AACFlow
Community support plus Enterprise 'Dedicated Support' (источник: AACFlow Pricing Page, откроется в новой вкладке)Community plus an unquantified "Dedicated Support" flag on the Enterprise plan. Enterprise and pricing pages do not include CSM, onboarding/enablement, or professional-services details beyond a plan-comparison-table "Dedicated Support" flag.
n8n
Forum on all tiers, dedicated on paid (источник: n8n Pricing, откроется в новой вкладке)Community forum (all tiers), plus direct/dedicated support on paid tiers. n8n's pricing page lists 'forum support' for Starter, escalating access on Pro/Business, and 'dedicated SLA support' at Enterprise; a separate n8n Help Center / Support Center and Discord/GitHub serve as community channels.
SLA
AACFlow
(источник: AACFlow Pricing Page, откроется в новой вкладке)Yes: the Enterprise plan includes a "Dedicated Support" feature per the pricing plan-comparison table; no SLA terminology, response-time, or uptime figures are published on the enterprise or pricing pages
n8n
(источник: n8n Pricing, откроется в новой вкладке)Yes: SLA-backed support only on the Enterprise plan. n8n's community support materials state there are no SLAs or severity-based prioritization for non-Enterprise customers. A documented SLA with response-time guarantees (contractually defined; community sources describe P1 targets in the 1-4 hour range) is only available to Enterprise customers.
Сообщество
AACFlow
(источник: AACFlow Landing Page, откроется в новой вкладке)No community size is published yet
n8n
~195k GitHub stars, 200k+ community members (источник: GitHub API: n8n-io/n8n repo, откроется в новой вкладке)Large community: ~195k GitHub stars, 200k+ community members across all channels. The n8n-io/n8n GitHub repository shows 195,690 stargazers (via GitHub API). n8n's own homepage advertises 200k+ community members in aggregate across its Discord, forum, and other channels, but does not break that figure down by channel, and neither the n8n Discord server nor the official Community Forum (community.n8n.io) publishes an individual member-count total.
Академия / обучение
AACFlow
(источник: AACFlow Docs: Academy, откроется в новой вкладке)Yes: AACFlow Academy is a dedicated structured-learning section of the docs site, separate from reference documentation and the API reference
n8n
(источник: n8n Academy, откроется в новой вкладке)Yes: n8n runs an official n8n Academy (learn.n8n.io) with structured, hands-on courses (e.g. N8N101 Essentials, N8N102 Integrations) offering badges and certificates of completion, plus a free beginner certification course.. Includes N8N101/N8N102 learning paths, quizzes, badges, and certificates; separate from ad hoc docs/blog content.
Сильные стороны AACFlow
AI Copilot / Chat agent-building surface (источник: AACFlow Docs: Copilot, откроется в новой вкладке)
Chat builds and manages work across the workspace; in-editor Copilot edits a single workflow.
A workspace-wide natural-language surface (Chat) that can build workflows, manage data, and take actions across integrations, plus an in-editor Copilot scoped to building and editing a single workflow directly.Hybrid semantic + keyword knowledge base (источник: AACFlow codebase: KB schema + file-parsers, откроется в новой вкладке)
Combines vector and full-text search with configurable chunking across 11 file formats.
Built-in RAG with pgvector embeddings and a generated tsvector column for combined vector + full-text search, plus a token-based chunker with configurable chunk size/overlap and 11 supported file formats (csv, doc, docx, html, json, md, pdf, pptx, txt, xlsx, yaml).Native MCP client and server (источник: AACFlow Docs: MCP Deployment, откроется в новой вкладке)
Call external MCP servers as tools, or expose AACFlow workflows as an MCP server.
A dedicated MCP block lets any workflow call external MCP servers as a tool, and a serve/workflow-servers API surface lets AACFlow expose its own workflows as MCP servers.Fork a workspace into dev, qa, and prod environments (источник: AACFlow Docs: Workspace Forks, откроется в новой вкладке)
Fork, diff, and promote environments with mandatory credential remapping.
Fork a whole workspace into a dev/qa/prod-style child environment, preview a diff, and promote changes bidirectionally. Credential and env-var remapping is required on every promote, so secrets never cross environments silently.Human-in-the-loop approvals with durable resume (источник: AACFlow Docs: Human in the Loop Block, откроется в новой вкладке)
Pause a run for human approval and resume later via a durable snapshot link.
A dedicated block pauses a run and waits for a human-submitted approval form, backed by persisted execution snapshots so the run can resume later via a link, even after a server restart.Live multiplayer canvas editing (источник: AACFlow codebase: realtime presence handler, откроется в новой вкладке)
Real-time cursors, selections, and synced edits on the same canvas.
Real-time cursors, selection broadcasting, and synced concurrent edits over a dedicated realtime backend, so a team can build the same workflow together at the same time.Задокументированные ограничения n8n
AI Workflow Builder not yet available self-hosted or on Enterprise (источник: n8n Community: Introducing AI Workflow Builder (Beta), откроется в новой вкладке)
Beta AI builder is Cloud-only today; self-hosters can't use it.
The natural-language-to-workflow AI Workflow Builder is in beta and limited to Cloud Trial/Starter/Pro plans. Enterprise and self-hosted support is listed as planned for a future release, so self-hosters cannot use it today.No public SOC 2 report; only 'aligned to' SOC 2 (источник: n8n Trust Center, откроется в новой вкладке)
SOC 2 report is available only on request to enterprise customers.
n8n's security program is 'aligned to' the SOC 2 framework with annual independent audits, and the SOC 2 report is available to enterprise customers via the Trust Center, not published publicly.No RBAC or workflow sharing at all on the free Community edition (источник: n8n Pricing, откроется в новой вкладке)
Free Community edition has zero RBAC; AACFlow includes roles on every plan.
n8n's free, self-hosted Community edition has zero role-based access control; project roles and any workflow sharing require a paid Business or Enterprise plan. AACFlow includes baseline workspace and organization roles (admin/write/read) on every plan, including the free tier, and reserves only SSO/SAML/OIDC, audit-log export, and SLA-backed support for Enterprise.MCP tool access control is coarse, not a distinct governance layer (источник: MCP Client Tool docs, откроется в новой вкладке)
MCP tool access control is coarse, without fine-grained per-tool policy.
MCP nodes are first-party, but tool access control is limited to simple 'all tools / selected tools / excluded tools' modes on the MCP Client Tool node. There's no finer-grained, per-tool policy or guardrail tooling like the product's evaluation features offer elsewhere.Итог
Choose AACFlow if you want an AI workspace that treats AI agents as first-class citizens: native multi-LLM support, real-time multiplayer editing, environment promotion (dev/qa/prod), human-in-the-loop approvals, and enterprise governance (SSO, credential-level permissions, audit logs) built in rather than bolted on.
Choose n8n if you specifically need unlimited users on every plan, including the entry tier: n8n includes unlimited users on every plan, including the €20/month Starter tier, and bills by monthly workflow executions rather than by user seat: a full run start-to-finish counts once no matter how many nodes it contains.
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Часто задаваемые вопросы
AACFlow is an AI workspace where teams build, deploy, and manage AI agents visually, conversationally, or with code. n8n is a fair-code workflow automation platform combining a visual, node-based builder with custom code and built-in AI/agent nodes, available as a self-hosted or cloud-hosted product. Teams considering a switch typically weigh pricing model, and how AI-native the platform's agent-building experience is.
