# Dify Alternatives: 4 Options Compared (2026 Guide) By Kofi Mensah · 2026-10-17 · Source: https://www.activepieces.com/blog/dify-alternatives-4-options-compared-2026-guide --- The best Dify alternative depends on whether your agent must act in other systems or only answer questions. If it must act, such as updating records, sending messages or filing tickets, judge tools on whether they can reach those apps and pause for a human first, which is the kind of check you can run on workflow builders like [Activepieces](https://www.activepieces.com) as easily as on any other. If your agent mostly chats over documents, Dify may still fit, and switching wouldn't cost you for nothing. Most vendor demos stop at an agent that talks well but can't touch your CRM or ticketing system. That is what a demo is. ## Dify alternatives: criteria, check date and quick answer ### Four criteria for comparing Dify alternatives You can compare the tools on one footing instead of on feature lists, because each gets the same four questions. The set comes from where agent projects tend to stall once they leave a prototype: - Apps the agent can act in: can it write to the tools your team uses, or only read from them? - Human approval step: can a person review and block an action before it happens? - Self-hosting: can you run it on your own infrastructure, so your data stays inside your boundary? - Price scaling with usage: does the bill stay predictable when runs multiply? Your job decides how these questions rank. A team in a regulated industry may treat self-hosting as a gate, while a small team may care mostly about the cost curve. Because an unchecked write action is the costliest mistake an agent can make, the approval question deserves close scrutiny. [Activepieces](https://www.activepieces.com), with **741 integrations** for an agent to act in, is measured this way on the same terms as the rest. Next, each platform gets these four questions in turn, with a note on where a gap matters and where it doesn't. ### How Dify alternatives were fact-checked in October 2026 In October 2026 I checked every vendor fact against the vendor's own pages, covering pricing, limits and documented behaviour. I didn't rely on third-party roundups or on what a sales demo implied. Where a vendor's page didn't state something clearly, I left the claim out instead of guessing. Pricing and features change often, so confirm anything that affects a purchase on the vendor's site before you commit. ![Activepieces pricing page with four subscription tiers showing features and monthly costs](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/5780ea9c-6ecc-45f7-99f2-8707dfb01930/vercel-pricing-in-2026-how-the-costs-scale-scree-22533578.webp) ## Why teams leave Dify for something else **The job changed; the product didn't fail**. That is why teams leave [Dify](https://dify.ai/blog/100k-stars-on-github-thank-you-to-our-amazing-open-source-community): a chat or retrieval app is one job, and acting inside business tools under approval is another. 10,000 GitHub stars in Nov 2023, 50,000 in Nov 2024, 100,000 in June 2025 and **158,660 today**: that is Dify's growth, [per GitStarClub](https://gitstarclub.com/langgenius/dify). That's a project still compounding, so nobody is leaving a dying tool; they're leaving a mismatch. ![Dify's GitHub stars since launch](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/60d9f784-fa62-4821-831d-c2c7b2f802d9/dify-alternatives-4-options-compared-2026-guide-37381911.svg "Source: GitStarClub") Dify is built around apps people talk to. Once the work becomes "update the CRM record, open the ticket, tell finance," each system needs its own custom tool or HTTP call, so every new action is code you now maintain. If an agent writes to business systems, it needs a human sign-off before it acts, plus per-person permissions, SSO and an audit trail. If a security review asks who changed which workflow and when, the answer depends on which controls your Dify edition includes. Check that list before assuming it covers you. ### Dify hosting and pricing surprises when self-hosting Self-hosting is where the bill shows up. ZCP documentation lists Dify at 4–8 GB of RAM, against 2–4 GB for n8n (a workflow automation tool) and 2–4 GB for Langflow (a visual builder for LLM pipelines), so you're facing **roughly double the infrastructure costs per instance**. ![Two servers, one with double the RAM modules](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/8b44120a-5d2d-42d2-a1b2-7693552d6964/dify-alternatives-4-options-compared-2026-guide-ebbf59d5.webp) At the top of those ranges, Dify needs a host twice the size, and that multiplies once you run separate development, staging and production copies. ### When staying on Dify is correct If your agent is mainly a chat interface, or answers questions from your documents, Dify's strengths are the ones you need. Prompt iteration by non-engineers, retrieval over a knowledge base and a quick path to a working app all fit that job. Moving costs you a migration, and without actions in other tools, approval steps or audit requirements, that cost buys you nothing. The extra RAM matters only if your hardware budget is tight. ## Flowise AI visual builder for agents **Its repository is now archived**, so it no longer receives updates. Flowise is a visual builder for LLM chains and agents, owned by Workday since its acquisition. ### Flowise pricing and self-hosting You can run Flowise on your own infrastructure because it is open source, and that is the part of the pitch that held up. What its own pages say about its current state is in the table. The takeaway is that you'd be adopting software that has stopped moving. | Fact | Value | Source page | |---|---|---| | Status | Archived 10 Aug 2026 | GitHub repository | | Owner | Workday acquisition, 14 Aug 2025 | Flowise site | | Stars | 55,498 | GitHub repository | | Self-hosting | Supported, you run it yourself | Flowise docs | ![Archived Flowise repository page with star badge](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/0ac2e09c-0339-417e-a783-d9b2328bd35e/dify-alternatives-4-options-compared-2026-guide-830cd4e0.webp) 55,498 stars show how many people adopted it. They say nothing about whether it will be maintained. For a self-hosted deployment, an archived repo means security patches and fixes to broken integrations are yours to carry. I won't quote a price here, because the cost that matters is the engineering time that replaces upstream maintenance. ### Flowise strengths and limits for agents On the canvas you wire together models, vector stores, document loaders and tools as nodes, and you can see how a retrieval chain is assembled. That's Flowise's strength, and it's useful when the job is a chat assistant over your documents. When the agent has to act inside business systems, the limit shows up. Its node catalogue centres on LLM components, and I couldn't confirm from its own pages the governance layer an acting agent needs: - role-based access - approval before a write - audit trails Add the archived status, and any gap you hit stays a gap. It suits a team that wants a visual retrieval or chat prototype on its own servers, and that has engineers willing to fork and maintain the code. It's a poor fit if the agent will touch customer records or send messages on someone's behalf, where you need a vendor shipping fixes and controls. ## Langflow open source visual builder Before you let it near customer records or outbound messages, look at Langflow's ownership chain. It is an open source visual builder for LLM and retrieval flows, and the product has changed hands twice in under a year. ![Corporate ownership of Langflow and Flowise](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/512c9d2c-26df-49b9-8d35-f5633f330a3c/dify-alternatives-4-options-compared-2026-guide-961a09bc.svg "Source: Workday (2025)") You can self-host Langflow, which keeps flow data and credentials on your own infrastructure. I'm not quoting a price here, because I couldn't confirm a current per-run or per-seat figure from its site and docs. Check the hosted tier's billing page before you model costs against run volume. Plan around ownership. According to [Nodesparks](https://www.nodesparks.com/data/automation-platform-pricing), DataStax bought Langflow on 2024-04-04, and IBM agreed to buy DataStax on 2025-02-25, per the [Workday announcement](https://newsroom.workday.com/2025-08-14-Workday-Acquires-Flowise,-Bringing-Powerful-AI-Agent-Builder-Capabilities-to-the-Workday-Platform) covering the wider market. In practice, a tool you chose from a startup is now a unit inside a large enterprise vendor, so its roadmap follows that parent's priorities, not yours. When Workday bought Flowise, a similar open source builder, on 2025-08-14, it followed the same pattern, per the [Newsroom](https://newsroom.workday.com/2025-08-14-Workday-Acquires-Flowise,-Bringing-Powerful-AI-Agent-Builder-Capabilities-to-the-Workday-Platform). Two of the best-known visual LLM builders **now sit inside corporate stacks** within a few months of each other. If you build on either, assume its direction will bend toward the parent's products, and keep your flows exportable. Composing LLM pipelines visually is Langflow's strength: - models - vector stores and retrieval components wired together on a canvas - Python underneath when you need to drop into code That suits prototyping retrieval-heavy flows quickly. You hit the limit the section above flagged. Its focus is building the pipeline, and I found no documented approval step before an agent acts, so a human gate on an outbound action is something you would have to build around it. It suits developers who want a visual way to assemble and iterate on retrieval and chat flows, and who are comfortable running and patching it themselves. It fits less well when the job is acting across business tools under approval and audit requirements, or when you need a vendor commitment that outlasts one acquisition. ## n8n platform Priced per workflow execution and licensed so you can self-host it for your own internal use, n8n is a workflow automation tool with a built-in AI Agent node. That makes it a different starting point from a chat-app builder: the agent is one node inside a workflow, not the product. One execution is one complete workflow run, however many steps it contains, and n8n's cloud plans meter by execution. An agent that loops through tool calls inside a single run costs the same as a simple two-step flow, which makes budgeting predictable. But a webhook firing on every inbound ticket, or any similar high-volume trigger, will push you up the plan ladder even when each run is trivial. You can self-host through the Community Edition, but the license is n8n's Sustainable Use License, which is source-available rather than open source in the OSI sense. It permits internal business use and restricts offering n8n to others as a hosted service. Check that against your plans if you're an agency or build products on top of it. Per n8n's pricing page, governance features such as SSO and environments sit in paid or enterprise tiers, not the free self-hosted build, so the self-hosted option doesn't by itself cover your access-control needs. The strength is breadth with escape hatches. The library of built-in app nodes is large, and the HTTP Request node covers anything without a dedicated node. You can wire those same nodes in as tools for the agent, so it acts in real systems instead of only answering questions. Once the agent holds those tools, control over what it does is the limit. n8n documents human-in-the-loop approval for tool calls, but you have to design where it applies. **Nothing makes it the default, so an agent with write access to a CRM can act unattended until you add the gate.** Test that path before you trust it. It suits technical teams that already think in workflows, want to run the engine on their own servers, and are comfortable with the license terms. It suits a team less well if it needs the governance layer included without moving to a higher tier. ## Activepieces Activepieces puts RBAC, SSO, SCIM, audit logs, log streaming, environments and git sync in the same product as the automation, self-hosted or on cloud, and its agent step works across 741 integrations, which means you won't need custom integrations for most platforms. ### Where the AI agent step fits Here the agent is a step inside a workflow, not the workflow itself. It can't act anywhere it has no connection to, so the useful question is what it can reach. ![A workflow automation flow with five steps including email trigger, AI processing, Slack approval, and routing logic.](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/57ac0ae0-3335-432a-afff-ffb303b7667d/model-security-vs-data-security-in-ai-workflows-f3455e93.webp) One agent can read a ticket in one tool, update a record in another and post the result somewhere a person will see it, because the agent step works across the 741 integrations in the [Activepieces pieces library](https://www.activepieces.com/pieces), roughly 60% of them community-contributed. Around the agent, everything stays deterministic: triggers, branches, retries and error handling are ordinary workflow steps, so the model is only trusted with the part that needs judgment. That's a narrower promise than a general autonomous agent, and I'd treat it as the more honest one. ### Approval, self-hosting and pricing You place the approval as a step before the action that matters, so the agent proposes and a person releases it. You choose where that gate sits; it's not a setting that covers everything automatically. ![Conveyor belt with a single gate where a person inspects a parcel](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/25a0edab-3f2f-4be0-ba9a-6b06923bf4dc/dify-alternatives-4-options-compared-2026-guide-9becb0d9.webp) Because the product is open source, you can run it on your own infrastructure or use the cloud version. The governance features (RBAC, SSO, SCIM, audit logs, log streaming, environments and git sync) are meant to sit together in either. Check the current pricing page for how runs are billed on your plan before you commit a high-volume job, since I won't quote numbers I can't point at. If you want to see how it behaves on your own tools, [try it free](https://cloud.activepieces.com/sign-up). ### Main limit and who it suits Activepieces builds workflows that act across its 741 integrations rather than chat apps over a knowledge base, so if your job is a chat app or retrieval tuning, Dify's focus fits better. That is the flip side of the design. Activepieces suits teams whose agent has to act across business tools under real governance, and who want that without stitching several products together. MoneyGram, Moneypenny, Alan and FundingSocieties run it. ### Dify alternatives comparison table Side by side, the table below puts all five tools in one view. It covers price, core strength, main limit, who each suits, and the four criteria from earlier, so you can see where each one gives something up. | Tool | Price | Core strength | Main limit | Who it suits | Apps the agent can act in | Human approval | Self-hosting | Pricing scales with runs | |---|---|---|---|---|---|---|---|---| | Dify | Free self-hosted; paid cloud tiers | Chat apps and retrieval | Governance sits behind higher tiers | Chat and knowledge-base builders | Fewer, mostly via tools and APIs | Possible, built by hand | Yes | Depends on tier | | Flowise | Free open source; paid cloud | Visual LLM chains and agents | Thin governance | Developers prototyping flows | Through custom tools | Limited | Yes | Depends on plan | | Langflow | Free open source; hosted options | Visual building for retrieval and agents | Governance is not its focus | Developers building retrieval-heavy flows | Through components | Limited | Yes | Depends on plan | | n8n | Free self-hosted community edition; paid cloud | Broad workflow automation | Some governance is paid-tier | Technical teams automating tools | Wide integration library | Possible in workflow | Yes | Per execution on cloud | | Activepieces | Free open source; paid cloud | Workflow-first agents across integrations | Not a chat or retrieval builder | Teams needing governed actions across tools | 741 integrations in the pieces library | Approval step | Yes | Check current plan | Read down the last four columns before the first five: the tools mostly differ in how much you must assemble yourself, and that decides which one fits your job. For teams that need governance and automation in one product, Activepieces is the better choice. RBAC, SSO, SCIM, audit logs, log streaming, environments and git sync all ship in the same platform as the workflows, self-hosted or on cloud, with no cut-down version of either. ![Activepieces homepage showing flexible AI workflow automation for technical teams with hero graphic and use case cards.](https://ap-marketing-media.fra1.cdn.digitaloceanspaces.com/uploads/ba8592d6-bc9a-4ace-83e4-839c44f8d423/comparing-clickup-alternatives-for-2026-screensh-deedd788.webp) Its agent step also works across the 741 integrations in its pieces library, so one agent can read, update and post across tools without custom integrations for most platforms. The judgement rests on that governance list being complete and delivered together, and a team that needs only one of those pieces may find a single-purpose tool sufficient. ## Frequently asked questions ### Is there a free open source alternative to Dify? Yes, several, though "open source" covers different licences, so check the one you'd depend on. Flowise and Langflow are open source and free to run yourself. Activepieces has an MIT-licensed core, while its enterprise directories (`packages/ee/`) sit under a separate commercial licence. n8n uses a source-available licence that restricts some commercial uses, which matters if you plan to resell or embed it. ### Can I migrate my Dify apps to another platform? Not with a click. Dify exports an app as a definition file, but the other tools don't read that format, so you rebuild the workflow. What carries over by hand is the part that took the most thought: your prompts, model settings and the source documents behind your knowledge bases. Budget for re-testing, because retrieval behaviour changes when chunking and embedding defaults change. Start with the simplest app and treat it as a pilot for the rest. ### Which Dify alternative can I self-host? You can self-host Flowise, Langflow, n8n and Activepieces on your own infrastructure. The difference is what you get once they're running. Check whether SSO, role-based access, audit logs and git sync are included in the self-hosted build or reserved for a paid licence, since that's where the tools diverge. Activepieces is built to run self-hosted or in its cloud with the same feature set, and its integrations are listed at https://www.activepieces.com/integrations. If you'd rather test before installing anything, you can try it free at https://cloud.activepieces.com/sign-up. ### Do I need code to use these alternatives? For most jobs, no. Each tool has a visual builder where you connect steps and fill in fields. Code becomes necessary at the edges: a custom API with no ready-made integration, awkward data reshaping, or a bespoke retrieval pipeline. Langflow and Flowise lean toward developers assembling AI components, while Activepieces and n8n have code steps you can skip until a workflow needs one. ## Related reading - [ChatGPT Apps SDK: How to Build Business Workflows](https://www.activepieces.com/blog/chatgpt-apps-sdk-how-to-build-business-workflows) - [Open Source Alternatives to Azure Logic Apps](https://www.activepieces.com/blog/open-source-alternatives-to-azure-logic-apps) - [SAP Business One AI Agents: Build a Chat Automation](https://www.activepieces.com/blog/sap-business-one-ai-agents-build-a-chat-automation) ## References - [GitStarClub](https://gitstarclub.com/langgenius/dify) - [ZCP documentation](https://docs.zcp.zsoftly.ca/public-cloud/marketplace/dify/) - [Workday](https://newsroom.workday.com/2025-08-14-Workday-Acquires-Flowise,-Bringing-Powerful-AI-Agent-Builder-Capabilities-to-the-Workday-Platform)