Dify vs Flowise vs Langflow: which fits your team after Flowise was archived
If your team is shortlisting visual LLM builders, treat Flowise as a poor choice for new builds. Its repository was set to read-only on August 13, 2026, and the core team ended its presence on August 31, 2026, so no further releases, security fixes or issue triage will come from the FlowiseAI core team. The code remains on GitHub under Apache 2.0, but files under packages/server/src/enterprise and files with an explicit copyright notice, such as IdentityManager.ts, are under a commercial license, so any fork must account for them. Dify and Langflow are the options still under active maintenance, and they serve different builders.
Dify fits teams that need RAG pipelines, agents, app publishing and a multi-service self-hosted stack. Its Docker Compose deployment starts PostgreSQL, Redis, Weaviate, Nginx and a code sandbox alongside the API, worker and web services, and the documentation asks for at least 2 CPU cores and 4 GiB of RAM. Its modified Apache License 2.0 forbids operating a multi-tenant environment from the source without written authorization, so check that rule against your plans. Langflow fits Python-centric teams that want an MIT-licensed builder, Python-customizable components and flows served as an API or an MCP server. Its current release is v1.12.6, published October 13, 2026, and its docs recommend PostgreSQL over the default SQLite for production.
Flowise still matters for existing installs. Confirm the version you run, the database behind it (SQLite is the default, with MySQL, PostgreSQL and MariaDB also supported), and whether your flows depend on enterprise code. Then choose between three paths: keep the frozen release (the last one is flowise@3.1.4, dated July 29, 2026) behind strict network controls, maintain your own Apache 2.0 fork with an owner for security patches, or migrate flows to Dify or Langflow. Migration is a rebuild rather than a file copy, so inventory every flow, tool and credential before you pick a target. The Future of Flowise discussion is the place to check the archive's stated terms.
Which platform fits which team situation
This table maps common team situations to the platform that fits best and the condition that decides it. Read each row against your own constraints: the deciding condition is what would change the answer. The main takeaway is that Flowise is a poor default for new work now that its repository is archived, while Dify and Langflow suit different builder profiles.
| Team situation | Best fit | Deciding condition |
|---|---|---|
| New internal AI assistant with RAG | Dify | Built-in RAG pipelines, a prompt IDE and app publishing cover this use case directly. The Community edition is limited to a single workspace, so confirm that one workspace is enough for your rollout. |
| Python-led developer team | Langflow | Components are customizable in Python, and the MIT license places few conditions on internal use. Plan a PostgreSQL database for production, since SQLite is the default. |
| Team already running Flowise | Migrate off Flowise, starting with a fork or a Dify pilot | The repository is archived and read-only, with no further releases or security fixes from the core team. Plan internal patching or a move to Dify or Langflow before relying on it. |
| Multi-tenant or resale use | Confirm licensing before choosing Dify | Dify's modified Apache 2.0 license requires written authorization to run a multi-tenant environment from its source. Langflow (MIT) and Flowise (Apache 2.0 outside enterprise code) carry different conditions, so check each license against your model. |
| Team needing SSO and multi-workspace control | Dify Enterprise | The Community edition is single-workspace. Enterprise adds SSO, multiple workspaces and professional support, with custom pricing. Ask the vendor which SSO protocols and identity providers apply to your setup. |
| Small pilot on a single host | Dify or Langflow | Dify Community needs at least 2 CPU cores and 4 GB of RAM plus Docker Compose 2.24.0 or later. Langflow can run with its default SQLite database, which suits a short pilot but not long-term production use. |
What each license allows and what is paid
Dify is released under the Dify Open Source License, a modified Apache License 2.0. The base terms are familiar, but two conditions matter for most teams. You need written authorization from LangGenius to use the source code to operate a multi-tenant environment, where one tenant is one workspace. You also may not remove or modify the logo or copyright information in the Dify console without a commercial license. Internal use of a single-workspace deployment falls outside those restrictions.
- Community edition: Free to self-host, and limited to a single workspace.
- Enterprise edition: Custom priced by quote. It adds SSO, multiple workspaces, advanced security, a commercial license and professional support.
- Multi-tenant operation: Running one Dify instance that serves several separate customers or business units as separate workspaces needs written authorization.
- Console branding: Removing the logo or copyright in the console requires a commercial license.
- Recurring cost: Enterprise is a subscription quote, while Community carries no license fee but still costs infrastructure and staff time.
Before you commit, confirm with LangGenius whether your planned internal or customer-facing use counts as multi-tenant operation, and get the answer in writing.
Flowise is split-licensed. Most of the repository is Apache 2.0, but the project's LICENSE.md places packages/server/src/enterprise under a commercial license, along with any file that carries an explicit copyright notice, such as IdentityManager.ts. Reading the Apache 2.0 label alone would miss these carve-outs. The repository has also been archived and is read-only, so the license question now sits alongside a maintenance question.
- Apache 2.0 code: The majority of the server, UI and components packages fall under Apache 2.0 and remain available on GitHub.
- Commercial enterprise code: Anything under packages/server/src/enterprise needs a commercial license to use.
- Explicit copyright files: Files such as IdentityManager.ts carry their own notice and are not covered by the general Apache 2.0 grant.
- Forks: The maintainers encouraged teams to fork for internal updates, so a fork inherits the same license split.
- Ongoing risk: No core-team releases or security fixes arrive after the archive, so any fix you need is your own work.
Ask your legal team to map every file you deploy against LICENSE.md, and confirm whether any enterprise path is active in your configuration.
Langflow is released under the MIT license. That is the most permissive of the three, and it allows internal use, modification and redistribution, including inside a commercial product, as long as the copyright and license notice are kept. The license covers the project as a whole, so there is no separate enterprise tier in the repository to track. Cost questions shift to hosting, support and the time your team spends operating the platform.
- Internal use: Running flows for your own staff or systems needs no license fee.
- Embedding in a product: MIT permits bundling Langflow into a product you sell, provided the notice is retained.
- Notice retention: Keep the MIT copyright and permission notice with any redistributed copy.
- Third-party components: Dependencies and integrations carry their own licenses, so review them in your build.
- Recurring cost: Costs come from infrastructure, upgrades and any support contract you choose to buy.
When you plan a product that resells AI features, have counsel review the dependency tree, since the Langflow license is clear but the packages it pulls in are not all identical.
What the Flowise archive means for existing installs
The Flowise archive is already in effect, and the timeline matters for any existing install. The maintainers announced a code freeze on July 29, 2026, archived the GitHub repository to read-only status on August 13, 2026, and ended core team presence on August 31, 2026. The last release, flowise@3.1.4, dates from July 29, 2026. Since the archive, no further releases, security fixes or issue triage come from the FlowiseAI core team. Any Flowise server you run today is therefore a frozen build, and every vulnerability disclosed after the freeze will stay open in the upstream code unless someone else patches it. Start by inventorying which hosts run Flowise, which version each one runs, and which packages and Node.js runtime they depend on, so you can judge exposure before anything else changes.
The announcement encourages teams to fork the repository, and the source code remains on GitHub under Apache 2.0. A fork lets you keep internal patches and dependency updates under your own control, but it also makes you the maintainer. Before choosing that path, confirm who on your side will review upstream components, rebuild images and test flows after each change. Check the license file too: content under packages/server/src/enterprise and files with an explicit copyright notice, such as IdentityManager.ts, are under a commercial license rather than Apache 2.0. If your team uses any enterprise-licensed functionality, verify your rights to those files before you redistribute a fork or build it into a shared image, and ask the Flowise project or its licensor to confirm the terms that apply to your use.
If you keep Flowise running for now, treat it as a contained, unpatched service: restrict network access, keep it off the public internet, and put its database (SQLite, MySQL, PostgreSQL or MariaDB) under regular backup. Decide on a migration path in parallel. Dify and Langflow both have active release trains, so an exit plan can be evaluated against their current releases rather than against a frozen Flowise build. Export or document each flow now, since the exported structure is what you will rebuild or port. The duration of any move depends on how many flows, custom nodes and integrations you have, so size it from your own inventory and ask any implementation partner for a written scope before committing dates.
What drives the running cost of each platform
Running cost is mostly labor and infrastructure, and it splits differently for each platform. Dify carries a fixed container footprint and an enterprise license question, Langflow's cost depends on how you set up its database and high availability, and Flowise's cost now sits with your own team because upstream maintenance has stopped.
Dify container footprint
The Docker Compose guide asks for at least 2 CPU cores and 4 GiB of RAM before you load a single knowledge base. That baseline comes from PostgreSQL, Redis, Weaviate, Nginx and the code sandbox running alongside the API, worker and web services. Your infrastructure bill is the host or cloud instance that carries these containers, plus storage and backups for the databases. Ask the vendor or your platform team to size the host for your expected concurrent users and document volume, and to confirm which vector store you will run.
Langflow database and high availability
Langflow uses SQLite by default, and its docs say PostgreSQL is better suited for production because of concurrent users, data integrity and scalability. Moving to PostgreSQL adds a database to operate, back up and patch. Kubernetes is the documented route for production-grade high availability, which adds cluster and platform engineering time on top of the application itself. Confirm with your team whether a single Docker host with PostgreSQL meets your availability target before you commit to a cluster.
Flowise self-maintenance after archive
Flowise's repository has been read-only since August 13, 2026, so security fixes and dependency updates no longer come from the core team. The software stays Apache 2.0 for the open code, but every patch, vulnerability response and Node.js upgrade now falls to your staff or a forked community project. Price this as recurring engineering time, and remember that enterprise code under the commercial license stays out of reach for a fork without a separate agreement. Ask any partner quoting maintenance to name who owns each fork decision.
Dify Enterprise quote versus Community
The self-hosted Community edition is free but limited to a single workspace. Enterprise is custom priced and adds SSO, multiple workspaces, advanced security, a commercial license and professional support. Your cost is therefore driven by the number of workspaces you need, whether you operate multi-tenant use, and whether you need the commercial license for console branding changes. When requesting a quote, ask what is one-time versus annual, what support hours are included, and whether Kubernetes deployment help is in scope.
Dify upgrade cadence
Dify has shipped minor releases roughly monthly, with 1.16.0 on July 17, 2026 and 1.17.0 on August 25, 2026 following it. Each upgrade means a staging test of the workflows, the vector store and the database migrations before production. A monthly cadence turns into recurring labor unless you schedule it. Ask for the upgrade method, rollback plan and retainer scope in writing, and confirm who tests your custom plugins and integrations after each release.
Langflow release pace and patching
Langflow publishes weekly patch releases, with v1.12.6 on October 13, 2026. Frequent patches lower the risk of falling far behind, but each one still needs a regression check for your custom Python components and flows. Build that check into your normal change process rather than treating it as a one-off project. Confirm that your team or partner can run the upgrade on the schedule the patch stream sets.
Moving existing Flowise flows to Dify or Langflow
The first decision is whether Flowise stays in production for a short window or whether flows get rebuilt now. Flowise's repository is archived and read-only, so no further releases or security fixes come from the core team, and the last release, flowise@3.1.4, dates to July 29, 2026. Teams that need time can fork the repository under its Apache 2.0 license and maintain an internal build, but that build becomes their own patching responsibility. Keep in mind that the enterprise code under packages/server/src/enterprise is under a commercial license, so a fork that depends on those files carries a separate license condition to confirm. Set a date for the cutover and record who owns security patches until then.
What transfers is usually the easiest part: system prompts, the text of templates, the choice of model provider, retrieval settings such as chunk size and top-k values, and the list of tools an agent may call. What must be rebuilt is the node graph itself, because Flowise node types, credentials and custom components do not map one-to-one to Dify's workflow nodes or Langflow's Python-based components. Custom Flowise nodes need a rewrite in whichever target you choose. Vector stores and document loaders also need to be re-indexed and their connection settings re-entered, since secrets are not portable. Confirm the export path for your Flowise version against the current documentation of Dify and Langflow, because export and import formats change between releases.
Test every flow against recorded inputs before it replaces the Flowise original. Build a small set of representative questions per flow, store the Flowise answers, and compare retrieval sources, tool calls and final outputs in the target. Flows that call external APIs or write to internal systems need a separate check of credentials and network egress, since the target platform will run them under its own service accounts. Plan to run both systems in parallel for a period that your team sets, and retire the Flowise instance only after the comparison shows acceptable results for each flow. Document the differences in a migration log so auditors and future maintainers can trace why each flow changed.
How to implement each platform in your own infrastructure
This sequence takes a team from platform choice to a tested pilot that stays inside its own network, with each step ending in a check the team can confirm before users arrive.
Choose the platform from the scenario table
The platform owner and the architecture lead agree which of Dify, Flowise or Langflow fits the pilot, using the scenario table earlier on this page. Flowise is only a candidate for teams that already run it and accept that no core-team releases or security fixes will come from the FlowiseAI core team after August 2026, so the choice usually narrows to Dify or Langflow for new work. Done means a written decision record names the platform, the pilot use case, the licenses reviewed and the owner who signs off. Confirm the license terms against the LICENSE file in the repository before the record is signed, because Dify's modified Apache License 2.0 restricts multi-tenant operation and console branding changes.
Size hosts against Dify's minimum requirements
The infrastructure team sizes the host or cluster before anything is installed. For a Dify Docker Compose deployment, the official guide asks for at least 2 CPU cores and 4 GiB of RAM, and the stack starts PostgreSQL, Redis, Weaviate, Nginx and code sandbox containers alongside the API, worker and web services, so the pilot host should be sized above that floor for the expected users and knowledge base volume. Langflow and Flowise have lighter default footprints but still need sizing for concurrent use. Ask the vendor or the deployment docs for current figures for the version you select. Done means a host sheet lists CPU, memory, disk and network for each platform, with the Docker Compose version confirmed as 2.24.0 or later for Dify.
Set the production database and object storage
The platform engineer replaces default local storage with a production database before real data goes in. Langflow uses SQLite by default, and its own docs say PostgreSQL is better suited for production because of concurrent users, data integrity and scalability. Flowise defaults to SQLite when no database variables are set, and it also supports MySQL, PostgreSQL and MariaDB. Dify ships with PostgreSQL as the metadata database and can use S3-compatible or other storage for files. Done means the database connection is tested, backups of the database are confirmed to restore into a scratch environment, and the team has written down which storage and vector store the pilot uses, since Dify defaults to Weaviate.
Set secrets and admin credentials before first login
The security engineer writes the secret and admin configuration into the deployment, stored in the team's secrets manager rather than in shared files. For Dify, the SECRET_KEY signs session cookies and JWTs and encrypts OAuth credentials, and changing it after deployment logs out all users, so it must be generated once and kept under change control. For Langflow, official packages and Docker images disable automatic login by default and require a superuser password set through LANGFLOW_SUPERUSER_PASSWORD, so the variable must be set before the first start. Done means each platform starts with its secret set, the Langflow admin login works, and a test confirms that the Dify secret is stored in the vault with a documented rotation procedure that warns users of the logout effect.
Configure SSO and role access
The identity team connects the platform to the corporate identity provider. Dify's SSO with OpenID Connect, SAML and OAuth2, including providers such as Microsoft Entra ID and Okta, is documented for Dify Enterprise, so teams on the Community edition should confirm in writing whether their chosen edition supports the integration they need, and whether the Community edition's single-workspace limit fits the pilot. Langflow and Flowise need the team to confirm what identity options their installed version provides and to plan for access controls at the reverse proxy if native SSO is not available. Done means a test user from each group signs in through the agreed path, and a list of who holds admin rights on each platform is reviewed.
Define the backup and upgrade routine
The platform owner sets the cadence for backups and version upgrades. Dify has published minor releases roughly monthly, with 1.17.0 on August 25, 2026 and 1.17.1 on September 10, 2026, so the team needs a standing test of each upgrade in a staging copy. Langflow's weekly patch releases and Flowise's archived status mean that Flowise installs will need a fork or internal maintenance plan if the team keeps it running. Done means a runbook covers database and object storage backups, restore tests, the upgrade path for each platform and the owner for each task. Ask each vendor or your support provider what an upgrade involves for your version before committing.
Run security testing before users arrive
The security testing team tests the pilot in the team's own environment before any business user is onboarded. Dify's recent security changes, including agent sandbox network isolation through a Squid proxy, token-based API authentication between services and sandboxed Jinja2 template rendering, should be checked against the deployed version rather than assumed. Testing should cover the public web entry point, API keys, the outbound proxy settings, the sandbox boundary and any connected model credentials. Done means a written test report lists findings, owners and fixes, and the team signs off that critical and high findings are closed. DeployOpen can plan and run this testing as a scoped engagement, but the client team owns the decision to launch.
Hand over to the operating team
The platform owner transfers the pilot to the people who will run it. The client's team needs staff who can operate Docker or Kubernetes, manage the database and secrets, read logs, apply upgrades and answer builders' questions about flows and apps. Who pays for each part matters: the license fee, if any, for the chosen edition, the infrastructure, the internal engineering time and any external support or retainer. Done means the runbook, host sheet, test report and access list are stored where the operating team can reach them, and an owner is named for each platform. Ask any implementation partner for a written scope that lists deliverables and handover documentation before work starts.
Questions teams ask before choosing a visual LLM builder
Is Flowise still safe to run in production?
Flowise is still running, but it no longer gets maintained by its core team, so treat it as a frozen dependency. The maintainers announced a code freeze on July 29, 2026, archived the repository to read-only on August 13, 2026, and ended core team presence on August 31, 2026. The last release, flowise@3.1.4, came out on July 29, 2026. No further security fixes or issue triage come from the core team. If you keep it, you own patching, which means forking the repository (the source remains under Apache 2.0) or planning a move. Check the Future of Flowise discussion before deciding how long an existing install can stay in service.
Can we use Dify Community for a company-wide tool?
Dify Community works for a single internal workspace, but the free self-hosted edition is limited to one workspace. The pricing page describes the Community edition as free and limited to a single workspace, so a company-wide tool with several separate teams usually points toward Enterprise. The license also matters here: the Dify Open Source License forbids operating a multi-tenant environment from the source without written authorization, where one tenant is one workspace. Internal use by one organization inside one workspace is the simpler case. Confirm the workspace count and tenancy model with LangGenius before rollout, because the answer depends on how you split teams.
What does Dify Enterprise add over Community?
Dify Enterprise adds the controls that a larger organization usually needs. According to the pricing page, the self-hosted Enterprise edition is custom priced and adds SSO, multiple workspaces, advanced security, a commercial license and professional support. The Enterprise SSO documentation lists OpenID Connect, SAML and OAuth2, with providers such as Microsoft Entra ID and Okta, and separate SSO scopes for workspace access and web app access. Dify Enterprise can also be deployed on Kubernetes for high availability. Ask the vendor for a written quote that lists which features and support levels are included, since pricing is not published.
Is Langflow production-ready on SQLite?
SQLite is fine for a single-user trial or a small test, but Langflow's own docs say PostgreSQL is better suited for production because of its support for concurrent users, data integrity and scalability. Langflow uses SQLite by default, so a production install needs an explicit database change before go-live. Also set LANGFLOW_SUPERUSER_PASSWORD, since official release packages and Docker images disable automatic login by default. For a multi-user rollout, plan HTTPS behind Caddy or Nginx and consider Kubernetes if you need high availability. Confirm your load test and backup approach against your own traffic before calling it production-ready.
How much effort is migrating from Flowise?
The effort depends on how many flows you have, which nodes they use and how much custom code sits behind them. Flowise stores its data in SQLite, MySQL, PostgreSQL or MariaDB, and the flows, credentials and vector connections all need mapping to the target platform. Dify and Langflow use different building blocks, so a flow rarely moves one for one. A practical first step is an inventory of flows, models, tools and data sources, followed by a pilot of two or three representative flows on the target. Ask any implementation partner for a written scope and timeline based on that inventory rather than a generic estimate.
Can our own team run these, or do we need outside help?
A team with Docker and database experience can run Dify, Langflow or Flowise for internal use, but the work is in the operations, not the first install. Dify's Docker Compose guide asks for at least 2 CPU cores and 4 GiB of RAM and starts PostgreSQL, Redis, Weaviate, Nginx and a code sandbox alongside the API, worker and web services, so you must patch, back up and monitor that stack. Langflow is lighter but still needs HTTPS, database and secrets setup. Outside help is most useful for a fixed-scope hardening, upgrade or migration plan, which DeployOpen scopes and quotes in writing. Decide early who owns upgrades and incident response.
How do the licenses affect internal use versus a customer-facing product?
Internal use is the simpler case for all three. Flowise's core code is Apache 2.0, with enterprise code under a commercial license, and Langflow is MIT licensed, so both allow broad internal use and customer-facing products built on the open code. Dify uses a modified Apache 2.0 license: operating a multi-tenant environment from the source, or removing the logo or copyright in the Dify console, requires a commercial license from LangGenius. If you plan to offer Dify-powered apps to outside customers from a shared environment, or white-label the console, get the licensing position in writing first. Have counsel review the license text for your use case.
How DeployOpen helps choose and implement the right builder
DeployOpen plans, implements, integrates, hardens, documents and supports self-hosted open-source platforms inside your own cloud accounts, data centers or air-gapped networks. For Dify vs Flowise vs Langflow, we start from your license, database and identity requirements, then build and hand over the option that fits your team.
How we scope
- We confirm which team builds flows, who approves them and which models and data sources they need.
- We check the Flowise archive status against any existing installs before recommending a migration path.
- Engagements are fixed-scope, with deliverables and timelines agreed in writing before work starts.
- We record license conditions for multi-tenant use and console branding in the written scope.
How we build
- We deploy the chosen builder with the database and vector store your scope requires, such as PostgreSQL or pgvector.
- We configure SSO, secret handling and outbound network controls to match your identity and security standards.
- We test flows, APIs and any exposed endpoints, including prompt injection and agent tool access where relevant.
- We migrate or rebuild existing Flowise or Langflow flows where the written scope includes that work.
How we hand over
- You receive documentation for deployment, configuration, backups, upgrade steps and known limitations.
- We prepare compliance-ready evidence and controls for your assessors, without issuing audit reports or certifications.
- Your staff are walked through day-to-day administration, flow ownership and the change process.
- We document the exit path so you can move flows or data if licensing or maintenance changes later.
How we support
- Ongoing support, upgrades and continuous testing are available as retainers after handover.
- Retainer scope covers tracking vendor releases, patching and re-testing after each upgrade.
- Ask any provider to confirm the maintenance status of the chosen builder and its license terms in writing.
- A quote follows from the written scope, so ask for each component, one-time and recurring, to be itemized.
