# Make vs n8n: the referee's guide to the visual automation cross-shop > Make's credit billing vs n8n's per-execution model, the self-hosting divide, AI agent maturity, and real user complaints — refereed as of July 2026. - Canonical: https://www.brahmalabs.io/compare/make-vs-n8n/ - Published: 2026-07-05 - Facts verified: 2026-07-05 - Author: Karthick Selvam - Publisher: Brahmalabs (https://www.brahmalabs.io) — note: Brahmalabs is a party or adjacent vendor; see disclosure at the end. **The short version:** Pick by workflow shape and hosting requirement, not feature lists. n8n bills a 50-step workflow as one execution and can run on your own hardware under a fair-code license; Make bills every module action as a credit, runs only in Make's cloud, and offers the gentler canvas with a far larger app catalog. If your real need is multi-day agentic runs with approval gates and long audit trails, both platforms will fight you — that is a different product category. ## Why this decision is harder than it looks Make and n8n are the two tools people genuinely cross-shop for visual automation, and the comparison is hard because their surfaces match while their structures are opposites. Both give you a drag-and-drop canvas, a large integration catalog, webhook triggers, and an AI agent feature. Underneath, they disagree about everything that determines your bill and your risk profile: Make charges [one credit per module action](https://www.make.com/en/pricing) and runs only in Make's cloud; n8n charges [one execution per full workflow run](https://n8n.io/pricing/) and can run on your own hardware under a [fair-code license with real conditions](https://docs.n8n.io/sustainable-use-license/). Neither disagreement shows up in a feature checklist. Both show up by month three. This piece referees the five axes that actually decide the purchase — pricing math, self-hosting, AI agent maturity, what users complain about, and enterprise posture — then gives choose-if guidance, including the case where neither fits. ## Pricing math: credits vs executions The single most consequential difference is the billing unit, so start there. Make bills in credits. The [official definition](https://www.make.com/en/pricing): "Each module action in your scenario, like adding a Google Sheet row or fetching Gmail account data, counts as one credit," and some AI-powered features "may use more." This unit is new. On [August 27, 2025, Make replaced "operations" with "credits"](https://help.make.com/coming-soon-credits-as-new-billing-unit-in-make) at a 1:1 conversion — with the important twist that AI and advanced modules now consume variable credits based on AI tokens, file size, or run time. Then on [November 6, 2025, extra-credit purchases were unified at a 25% markup](https://community.make.com/t/important-update-adjustment-to-plans-and-pricing/94578) over included credits. Make does not publish exact credit consumption for agent steps, so agent-heavy scenarios draw down quota at a rate you discover by running them — a dynamic third parties have summarized as ["why your automations suddenly cost more"](https://dev.to/alifar/makecom-credits-explained-why-your-automations-suddenly-cost-more-4dho). n8n bills per execution: [one execution is a single run of your entire workflow](https://n8n.io/pricing/), regardless of how many steps it contains or how much data it moves. A 50-step workflow costs exactly one execution. Your LLM spend rides on your own provider keys and never touches the execution count. Here is the current shape of both price lists. All figures are as of July 5, 2026; n8n shows prices regionally, and these are EUR as displayed to a European visitor — resist converting them. | | Make | n8n Cloud | |---|---|---| | Billing unit | [1 credit per module action; AI features variable](https://www.make.com/en/pricing) | [1 execution per full workflow run](https://n8n.io/pricing/) | | Free option | [Free plan: 1,000 credits/mo, 2 active scenarios](https://www.make.com/en/pricing) | [No permanent free cloud tier](https://n8n.io/pricing/); self-hosted Community Edition | | Entry paid plan | ["Make" plan from $9/mo for 5,000 credits](https://www.make.com/en/pricing) | [Starter €20/mo for 2,500 executions, 5 concurrent](https://n8n.io/pricing/) | | Scaling up | [Usage slider to 8M+ credits; Enterprise custom](https://www.make.com/en/pricing) | [Pro €50/mo (10,000 exec.), Business €667/mo (40,000 exec.), Enterprise custom](https://n8n.io/pricing/) | | Overage | [Extra credits at a 25% markup](https://community.make.com/t/important-update-adjustment-to-plans-and-pricing/94578) | Concurrency-capped per plan rather than marked up | | Run history | [7/30/60 days by plan](https://www.make.com/en/pricing) | [Starter 2,500 executions/7 days up to Enterprise 50,000/unlimited](https://docs.n8n.io/manage-cloud/cloud-data-management/) | Note that Make's current lineup is Free, a single paid "Make" plan with a usage slider, and Enterprise. Third-party articles still describe legacy tier names that [no longer appear on the pricing page](https://www.make.com/en/pricing). Now the worked example. Suppose your core workflow has 50 steps and runs 100 times a month. On n8n Starter that is 100 of your 2,500 monthly executions — 4% of quota. On Make's $9 entry plan it is roughly 5,000 credits — your entire monthly allowance, before any variable AI consumption. Reverse the shape and the math flips: a two-module scenario firing thousands of times a month spends Make credits slowly, and Make's $9 entry point undercuts n8n's €20 floor for small workloads. The rule of thumb: Make's unit punishes workflow depth; n8n's unit ignores it. Two caveats keep this honest. First, n8n meters concurrency per plan ([5 concurrent on Starter, 20 on Pro, 200+ on Enterprise](https://n8n.io/pricing/)), so bursty workloads queue on cheap tiers. Make has no native per-scenario concurrency control at all — webhook runs process in parallel by default, and [users needing bounded parallelism build custom queues](https://community.make.com/t/how-to-limit-parallel-executions-create-a-custom-queue/40556), which cuts both ways. Second, at sustained volume the totals converge: [third-party math puts Make spend at 40k–80k credits/month, with the 25% overage premium, at or above the cost of a self-hosted n8n instance](https://trackstack.tech/en/make-com-pricing-2026/). ## The self-hosting divide This axis is binary, and it is the cleanest filter in the whole comparison. Make is a [closed-source, proprietary, cloud-only SaaS](https://www.make.com/en/pricing). No open-source edition exists, and no plan offers self-hosted deployment, because the platform is never distributed. The one on-premises component is the Enterprise-only ["on-premise agent"](https://www.make.com/en/help/connections/using-an-on-premise-agent) — a Java 11+ connectivity bridge that lets Make's cloud reach databases and apps inside your private network. Useful, but it is a network tunnel, not self-hosting. Data residency comes down to a choice of hosting zone: Make offers an [EU data center alongside US hosting, with the zone tied to the account](https://community.make.com/t/data-residency-for-european-customers/68767). n8n distributes its source. It is not OSI open source — the [Sustainable Use License](https://github.com/n8n-io/n8n/blob/master/LICENSE.md) is fair-code, and files marked ".ee." in the repo sit under a separate enterprise license. But the grant is substantial: [free use, modification, and self-hosting for internal business purposes](https://docs.n8n.io/sustainable-use-license/), with commercial consulting on top of it explicitly allowed. What the free license forbids is also concrete: hosting one instance and charging clients to run automations on it, white-labeling, or offering n8n as a managed service — those require an embed or enterprise agreement. n8n publishes no embed price; [third-party analyses report it starting around $50,000/year](https://taskjuice.ai/blog/n8n-white-label-cost-agencies), so treat that figure as reported, not official. At scale, self-hosted n8n runs a real distributed architecture: [queue mode pushes execution IDs through Redis to worker instances](https://docs.n8n.io/hosting/scaling/queue-mode/), with per-worker concurrency flags and multi-main failover. Self-hosting also carries its bill, paid in operations work rather than currency. Between December 2025 and January 2026, [n8n disclosed four critical vulnerabilities in roughly two weeks, including CVE-2026-21858 — CVSS 10.0, unauthenticated remote takeover of exposed instances — with public exploits circulating](https://thehackernews.com/2026/01/critical-n8n-vulnerability-cvss-100.html). Self-hosters had to patch urgently. If your team cannot commit to that response cadence, "we can self-host" is a liability dressed as a feature. Make's cloud-only model removes the choice — and the burden — entirely. ## AI agent maturity: a six-month-old canvas feature vs a LangChain toolkit Both vendors bolted agents onto workflow engines, from opposite directions. Make launched [AI Agents in beta on April 14, 2025](https://www.make.com/en/make-ai-agents-press-release), then shipped a rebuilt generation: [next-generation Make AI Agents went GA on February 11, 2026](https://www.make.com/en/blog/announcing-next-generation-make-ai-agents), built directly in the scenario canvas with a real-time Reasoning Panel, in-canvas test chat, multimodal file input and output, shareable agents, and a library of pre-built ones. That design goal is legible: agents as decision-making steps inside deterministic scenarios, testable where non-developers already work. It is also young — as of July 2026, the current agent product is under six months post-GA. Around it, Make shipped a [native AI Provider for LLM access without managing API keys, billed through credits](https://www.make.com/en/ai-agents), and [MCP in both directions: a server exposing scenarios as tools to Claude and ChatGPT, and a client letting scenarios call external MCP tools](https://developers.make.com/mcp-server). n8n's agent stack is older and deeper. The [AI Agent node is built on LangChain](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent) as a cluster of nodes — a root agent plus sub-nodes for model, memory, and tools — and [one agent can invoke another as a tool](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolaiagent), giving you multi-agent composition. The differentiator is testing: n8n ships [native Evaluations for AI workflows](https://docs.n8n.io/advanced-ai/evaluations/overview/) — light evaluations during development, metric-based evaluations in production, with built-in AI-judged correctness scoring and custom metrics. Make's published materials show no comparable evaluation feature — its in-canvas test chat is interactive testing, not metric-based evaluation. n8n also has [first-class MCP in both directions](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger), with SSE and streamable HTTP transports on the server trigger and OAuth2 on the client. The company's own framing is worth noting: its stated direction is ["AI orchestration" — combining AI, code, and humans in the same process — rather than fully autonomous agents](https://blog.n8n.io/series-c/). The honest read: n8n gives a technical team more control and, critically, a way to measure whether the agent works. Make gives a non-technical team an agent they can watch reason and test in the same canvas as everything else. Neither is built for agent processes that run unattended for days — both are workflow engines with agent steps, and their retention windows and approval mechanics (below) reflect that. ### Human approvals Approvals gate agent behavior, and the two platforms gate approvals differently. Make has a dedicated Human in the Loop app — create a review request, watch for approved/adjusted/canceled — but it is [only available on the Enterprise plan](https://www.make.com/en/integrations/human-in-the-loop-enterprise), so [non-Enterprise users typically hand-build approval loops with Slack buttons or Airtable review steps](https://www.xray.tech/post/human-in-the-loop-make). n8n offers [Send-and-Wait approval operations across Slack, Gmail, Microsoft Teams, Telegram, Discord, WhatsApp, and its Chat node](https://docs.n8n.io/advanced-ai/human-in-the-loop-tools/), with approval buttons, free text, or custom forms, plus gating for agent tool calls — documented as core node functionality with no plan gate mentioned. On this axis n8n simply wins: approvals are a core primitive rather than an enterprise upsell. ## What users actually complain about Vendor pages describe intent; complaints describe experience. The two products fail in different places. Make's complaints cluster around opacity. Aggregated review quotes report that ["error causes are not always obvious"](https://hackceleration.com/make-review), which stings because Make's error-handling machinery is genuinely capable — [five handler directives, stored incomplete executions for retry, automatic scenario disabling after three consecutive errors](https://help.make.com/overview-of-error-handling) — yet diagnosing why something failed remains the reported pain. The second cluster is billing anxiety: [a runaway or looping scenario "can burn your whole quota fast"](https://hackceleration.com/make-review), and with the 25% overage markup, an undetected loop is a real invoice event. Third: support, with users reporting ["absolutely no way to talk to a human"](https://hackceleration.com/make-review) on urgent quota and account issues below Enterprise. n8n's complaints cluster around ramp-up and operations. [G2 reviewers consistently flag a steep learning curve as the top drawback](https://www.g2.com/products/n8n/reviews) — error handling, sub-workflows, and code nodes demand real investment, especially from non-developers — along with undescriptive, technical error messages and JSON mapping that overwhelms anyone without a JavaScript background. Reviewers also [report missing cost-control features that produce unintended spend during learning and testing](https://www.g2.com/products/n8n/reviews). On the operations side, [independent assessments report performance struggles with many parallel workflows or large datasets, and note the free self-hosted version lacks advanced user management, detailed audit logs, and robust monitoring](https://latenode.com/blog/low-code-no-code-platforms/n8n-setup-workflows-self-hosting-templates/n8n-latest-version-2025-release-notes-changelog-update-analysis). The pattern: Make frustrates you after you have built the thing; n8n frustrates you while you are building it. Choose the frustration your team is better equipped to absorb. ## Enterprise posture On paper certifications, Make is ahead. Its security page states the [information-security program is ISO 27001 certified, with completed SOC 2 Type II and SOC 3 audits](https://www.make.com/en/security) — SOC 3 public, SOC 2 under NDA. n8n [aligns its security program to SOC 2 with annual independent audits](https://trust.n8n.io/), distributing reports through its trust center; no ISO 27001 certification was verifiable from official sources as of July 2026. Make's Enterprise tier adds [SAML SSO with domain enforcement, team-member audit logs, per-team credit limits, overage protection, 24/7 support, and an environment run in a separately managed AWS account isolated from self-serve customers](https://www.make.com/en/security). The ceiling to notice is retention: [run history caps at 60 days even on Enterprise](https://www.make.com/en/pricing), which is a hard limit on how far back an investigation can look. n8n's enterprise tier reads like it was written for platform engineers: [SSO/SAML/LDAP with provisioning, enforced 2FA, project-level access control with custom roles, external secrets managers (HashiCorp Vault, AWS Secrets Manager, Azure Key Vault), and isolated dev/prod environments with Git integration and workflow diffs](https://n8n.io/enterprise/). Its enterprise page [names customers including Microsoft, Deutsche Telekom, NVIDIA, Mercedes-Benz, and Vodafone](https://n8n.io/enterprise/). Vendor stability looks solid from the outside: a [$180M Series C at a $2.5B valuation in October 2025](https://blog.n8n.io/series-c/), followed by [SAP investing at a $5.2B valuation in May 2026](https://www.trendingtopics.eu/sap-bets-big-on-ai-invests-in-n8n-at-a-5-2-billion-valuation/). And on catalog breadth, present both vendors' own numbers and let them stand: Make claims [3,000+ apps](https://www.make.com/en/integrations) with [30,000+ actions](https://www.make.com/en/make-ai-agents-press-release) and a [template library showing 8,215 entries when fetched in July 2026](https://www.make.com/en/templates); n8n's [directory lists 1,921 integrations](https://n8n.io/integrations/) while its [GitHub repository — roughly 195,000 stars as of July 2026 — describes "400+ integrations"](https://api.github.com/repos/n8n-io/n8n), the smaller figure counting built-in nodes and the larger including credential and community listings. ## The decision ### Choose Make if - Your builders are ops, marketing, or agency people, not developers, and the [8,000+ public templates](https://www.make.com/en/templates) and 3,000+ app catalog map to their stack. - Your scenarios are short and event-shaped — a few modules firing often — where per-action credits stay cheap and the [$9 entry plan](https://www.make.com/en/pricing) undercuts n8n's floor. - Procurement needs ISO 27001 and SOC 2 Type II checked today, and cloud-only delivery with an [EU zone option](https://community.make.com/t/data-residency-for-european-customers/68767) is acceptable. - You want agents that non-developers can build and test inside the same canvas, and you accept that the [current agent generation is months old](https://www.make.com/en/blog/announcing-next-generation-make-ai-agents). ### Choose n8n if - Self-hosting is a hard requirement — for data residency, compliance, or cost — and your team can own the [patch cadence that recent critical CVEs demanded](https://thehackernews.com/2026/01/critical-n8n-vulnerability-cvss-100.html). - Your workflows are long and multi-step, where [one-run-one-execution billing](https://n8n.io/pricing/) makes depth free. - You have developers who want to drop into code, compose [LangChain-based agents](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent), and actually [evaluate AI workflow quality](https://docs.n8n.io/advanced-ai/evaluations/overview/) before shipping. - You need approval steps as core node functionality, not behind an enterprise gate. - You are an agency building inside each client's own instance — [explicitly permitted](https://docs.n8n.io/sustainable-use-license/) — rather than reselling a hosted instance, which is not. ### When neither fits Both platforms are event automation engines: something fires, a run executes in seconds to minutes, and the trace ages out — [in 7 to 60 days on Make](https://www.make.com/en/pricing), [by count-and-age caps on n8n Cloud's lower tiers](https://docs.n8n.io/manage-cloud/cloud-data-management/). If your workload is instead a process that lives for days — an agent drafts, a human reviews tomorrow, work resumes after sign-off, and compliance wants the full trail next quarter — you will feel the grain of both tools fighting you: approvals bolted on through chat messages or an enterprise-gated app, no durable pause primitive, short audit windows. ## Where Brahmalabs fits A disclosure-first aside: we build Brahmalabs, so weight this accordingly. Brahmalabs is for the workload in the paragraph above — durable agentic runs rather than event automation. Every run is a durable workflow that survives crashes and restarts, so a run that started yesterday can finish today, and an approval wait parks the run without burning compute; human approval is a first-class node with multi-party consensus, SLA timeouts, and escalation chains rather than a chat-message workaround; and every step lands in an append-only audit log across eight event categories, with each agent step executing in an isolated, resource-capped container whose actual outbound domains are captured per run. Candor requires the gaps: it is a young product in early access with no self-hosting today (if that is a hard requirement, n8n is honestly the better fit), SOC 2 Type II still in progress, and an integration catalog of hundreds of providers — not Make's thousands. If durable runs with approval gates and audit are the actual requirement, the free tier is a low-stakes way to check the fit. ## Where this leaves you Strip the marketing and the decision is mechanical. First, apply the binary filter: if self-hosting is mandatory, n8n is the only one of the two that can do it, license conditions and patching burden included. Second, if both remain, measure your workflow shape against the billing unit — count the steps in your three most important workflows and multiply by monthly runs; deep workflows point at n8n's executions, shallow frequent ones at Make's credits. Third, match the builder: developers will outgrow Make's canvas and appreciate n8n's code paths and evals; non-developers will stall on n8n's learning curve and ship faster on Make. And if what you are actually building is not automation but supervised agentic work — long-lived runs, human sign-off, auditable history — take that as a signal to look outside this pairing altogether, at the durable-execution category rather than event automation. ## Questions people actually ask ### Is n8n cheaper than Make? It depends on workflow length. n8n bills one execution per full workflow run regardless of steps (Starter is €20/month for 2,500 executions, shown in EUR to European visitors), while Make bills one credit per module action, from $9/month for 5,000 credits. A 50-step workflow costs one execution on n8n but 50 credits on Make, so long workflows favor n8n and short high-frequency scenarios can favor Make. ### Can you self-host Make? No. Make is a closed-source, cloud-only SaaS with no self-hosted or community edition on any plan. Its Enterprise-only 'on-premise agent' is a Java-based connectivity bridge that lets Make's cloud reach apps inside your network — it is not self-hosting. n8n, by contrast, can be self-hosted free for internal business use under its Sustainable Use License. ### Is n8n open source? Not in the OSI sense. n8n uses the fair-code Sustainable Use License: free to use, modify, and self-host for internal business or personal purposes, with enterprise-licensed files marked '.ee.' in the codebase. Hosting n8n for paying clients, white-labeling it, or embedding it in your product requires a commercial license. ### Which has better AI agents, Make or n8n? n8n's AI Agent node is built on LangChain, supports multi-agent composition, ships native evaluations for testing AI workflows, and speaks MCP in both directions — it is the deeper stack. Make's next-generation AI Agents went GA in February 2026 with a Reasoning Panel and in-canvas testing, and are the more approachable option for non-developers, but the product is under six months post-GA as of July 2026. ### Do Make and n8n support human-in-the-loop approvals? Both, with different gates. Make has a dedicated Human in the Loop app, but it is only available on the Enterprise plan; other users hand-build approval flows with Slack buttons or Airtable. n8n offers Send-and-Wait approval operations across Slack, Gmail, Teams, Telegram, Discord, WhatsApp, and its Chat node, with configurable timeouts — documented as core node functionality with no plan gate, unlike Make's Enterprise-only app. ### Is Make or n8n more enterprise-ready on compliance? Make states its security program is ISO 27001 certified and that it has completed SOC 2 Type II and SOC 3 audits. n8n aligns to SOC 2 with annual independent audits and distributes reports through its trust center, but no ISO 27001 certification was verifiable from official sources as of July 2026. n8n counters with self-hosting, which keeps data on your infrastructure entirely. ## Sources (checked 2026-07-05) - [Make pricing](https://www.make.com/en/pricing) — accessed 2026-07-05 - [Make help: credits as new billing unit](https://help.make.com/coming-soon-credits-as-new-billing-unit-in-make) — accessed 2026-07-05 - [Make community: plans and pricing adjustment (Nov 2025)](https://community.make.com/t/important-update-adjustment-to-plans-and-pricing/94578) — accessed 2026-07-05 - [Make credits explained (dev.to)](https://dev.to/alifar/makecom-credits-explained-why-your-automations-suddenly-cost-more-4dho) — accessed 2026-07-05 - [Make pricing analysis 2026 (Trackstack)](https://trackstack.tech/en/make-com-pricing-2026/) — accessed 2026-07-05 - [Make integrations](https://www.make.com/en/integrations) — accessed 2026-07-05 - [Make templates](https://www.make.com/en/templates) — accessed 2026-07-05 - [Make AI Agents press release](https://www.make.com/en/make-ai-agents-press-release) — accessed 2026-07-05 - [Make next-generation AI Agents announcement](https://www.make.com/en/blog/announcing-next-generation-make-ai-agents) — accessed 2026-07-05 - [Make AI agents](https://www.make.com/en/ai-agents) — accessed 2026-07-05 - [Make MCP Server developer docs](https://developers.make.com/mcp-server) — accessed 2026-07-05 - [Make Human in the Loop (Enterprise)](https://www.make.com/en/integrations/human-in-the-loop-enterprise) — accessed 2026-07-05 - [Human-in-the-loop workarounds in Make (XRay)](https://www.xray.tech/post/human-in-the-loop-make) — accessed 2026-07-05 - [Make community: limiting parallel executions](https://community.make.com/t/how-to-limit-parallel-executions-create-a-custom-queue/40556) — accessed 2026-07-05 - [Make security](https://www.make.com/en/security) — accessed 2026-07-05 - [Make community: EU data residency](https://community.make.com/t/data-residency-for-european-customers/68767) — accessed 2026-07-05 - [Make help: on-premise agent](https://www.make.com/en/help/connections/using-an-on-premise-agent) — accessed 2026-07-05 - [Make help: error handling overview](https://help.make.com/overview-of-error-handling) — accessed 2026-07-05 - [Make review with aggregated user quotes (Hackceleration)](https://hackceleration.com/make-review) — accessed 2026-07-05 - [n8n pricing](https://n8n.io/pricing/) — accessed 2026-07-05 - [n8n LICENSE.md](https://github.com/n8n-io/n8n/blob/master/LICENSE.md) — accessed 2026-07-05 - [n8n Sustainable Use License docs](https://docs.n8n.io/sustainable-use-license/) — accessed 2026-07-05 - [n8n white-label cost analysis (TaskJuice)](https://taskjuice.ai/blog/n8n-white-label-cost-agencies) — accessed 2026-07-05 - [n8n AI Agent node docs](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent) — accessed 2026-07-05 - [n8n AI Agent Tool sub-node docs](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolaiagent) — accessed 2026-07-05 - [n8n Evaluations docs](https://docs.n8n.io/advanced-ai/evaluations/overview/) — accessed 2026-07-05 - [n8n MCP Server Trigger docs](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger) — accessed 2026-07-05 - [n8n human-in-the-loop docs](https://docs.n8n.io/advanced-ai/human-in-the-loop-tools/) — accessed 2026-07-05 - [n8n integrations directory](https://n8n.io/integrations/) — accessed 2026-07-05 - [n8n GitHub repository (API)](https://api.github.com/repos/n8n-io/n8n) — accessed 2026-07-05 - [n8n queue mode docs](https://docs.n8n.io/hosting/scaling/queue-mode/) — accessed 2026-07-05 - [n8n cloud data management docs](https://docs.n8n.io/manage-cloud/cloud-data-management/) — accessed 2026-07-05 - [n8n enterprise](https://n8n.io/enterprise/) — accessed 2026-07-05 - [n8n trust center](https://trust.n8n.io/) — accessed 2026-07-05 - [n8n Series C announcement](https://blog.n8n.io/series-c/) — accessed 2026-07-05 - [SAP investment in n8n (Trending Topics)](https://www.trendingtopics.eu/sap-bets-big-on-ai-invests-in-n8n-at-a-5-2-billion-valuation/) — accessed 2026-07-05 - [Critical n8n vulnerability CVSS 10.0 (The Hacker News)](https://thehackernews.com/2026/01/critical-n8n-vulnerability-cvss-100.html) — accessed 2026-07-05 - [n8n reviews on G2](https://www.g2.com/products/n8n/reviews) — accessed 2026-07-05 - [n8n production analysis (Latenode)](https://latenode.com/blog/low-code-no-code-platforms/n8n-setup-workflows-self-hosting-templates/n8n-latest-version-2025-release-notes-changelog-update-analysis) — accessed 2026-07-05 --- Disclosure: this piece is published by Brahmalabs, an agentic-workflow platform adjacent to the products discussed. Facts are dated and linked to primary sources; corrections: hello@brahmalabs.io.