Best Dify Alternatives in 2026: Open-Source and Self-Hosted Options
Five Dify alternatives ranked for 2026 (Sim, n8n, LangChain and LangGraph, RAGFlow, and Langflow) on license, self-hosting, workflow depth, MCP support, and pricing.
Sim is the best overall Dify alternative in 2026 for teams that need broader workflow automation, tool-using agents, a permissive Apache 2.0 core license with separately licensed enterprise code, and MCP support in both directions. Choose n8n for integration-heavy technical automation, LangChain and LangGraph for code-first agent control, RAGFlow for document-heavy retrieval, and Langflow for Python-based visual LLM pipelines.
Dify remains a strong choice when prompt iteration, knowledge retrieval, and packaged LLM applications define most of the workload. Look beyond Dify when you need wider business-system automation or a standard permissive license without Dify's added multi-tenant and branding conditions.
This page ranks the wider field. If you have already narrowed the choice to Sim or Dify, the Sim vs Dify comparison covers that decision criterion by criterion.
The Dify alternatives ranking evaluates each platform against the same five buyer-relevant criteria: license, workflow depth, agent and MCP capability, deployment control, and commercial cost. We ranked broader automation and agent-building capability first because this page is for buyers who have already identified a reason to look beyond Dify's LLM-app and RAG focus.
Author: Andrew Caslow
Affiliation: Sim
Review basis: Official vendor documentation, pricing pages, license files, product documentation, and vendor-maintained repositories
Facts checked: October 5, 2026
Ranking rule: The highest-ranked product must provide the strongest overall fit across the published criteria, not merely the closest feature match to Dify
Prices, plan limits, product status, and license terms can change. All changing claims below were checked against primary vendor sources on the fact-check date.
A Dify alternative should solve the specific limitation that caused you to leave Dify without creating a larger licensing, deployment, or operational problem. Evaluate these five criteria before choosing a platform.
Dify alternatives with a standard permissive license create fewer product-specific restrictions than Dify's modified Apache terms. Dify's license requires written authorization to operate a multi-tenant service from its source and prevents removal or modification of the Dify console logo and copyright notices. Compare those conditions with Apache 2.0, MIT, or a source-available fair-code license based on your intended use.
A Dify alternative's workflow depth measures whether it can coordinate APIs, business tools, structured data, branching, schedules, and event-driven processes in addition to model calls and retrieval. Dify may remain the better fit when the application is primarily a prompt, knowledge base, or chatbot experience.
A Dify alternative's agent tooling should support tool use, controlled execution, and interoperable deployment. Model Context Protocol support matters when workflows must consume external tools, publish capabilities to other AI applications, or do both.
A Dify alternative's self-hosting path should include documented infrastructure requirements and a clear distinction between open-source, cloud, and enterprise features. Also confirm whether production workflows can be exposed through APIs, chat interfaces, or MCP tools.
Dify alternatives should be compared by billing unit, not just headline subscription. Credits, workflow executions, seats, traces, compute units, model tokens, and self-hosting infrastructure produce different cost curves.
LangChain and LangGraph: LangChain and LangGraph are MIT-licensed code frameworks for developers who want explicit control over agent state, branching, retries, persistence, and human review.
Flowise: Flowise's community code is under Apache 2.0 with separately licensed enterprise files, according to its license, but the maintainers announced the project's wind-down and August 31, 2026 end of life in the official repository discussion.
Haystack: Haystack is an Apache 2.0 code-first framework whose pipeline model connects retrieval, preprocessing, generation, routing, and custom components.
Sim combines deterministic workflow steps and model-driven agents in the same visual graph. Teams can connect 1,000+ integrations and keep predictable operations separate from decisions that require model judgment.
This makes Sim a broader automation alternative rather than a clone of Dify. Dify remains more specialized around prompts, retrieval, and packaged LLM applications; Sim is designed for workflows that must coordinate AI decisions with business systems and repeatable operational logic.
As of October 2026, Sim pricing is Free at $0 with 1,000 one-time credits; Pro at $25 per user per month with 6,000 monthly credits and a 2,000-credit weekly refresh; Max at $100 per user per month with 25,000 monthly credits and a 4,000-credit weekly refresh; and Enterprise at custom pricing with custom credits. The pricing page also offers a 15% annual-billing discount. Model-provider charges, local infrastructure, and other metered services should be considered separately from plan credits.
n8n is best for engineering-led teams that need broad API, database, and business-tool automation and can work within a source-available fair-code license.
n8n is a visual automation platform for connecting APIs, databases, business software, custom code, and AI steps. Its strength is breadth: teams can place model calls and agent nodes inside operational workflows for jobs such as ticket routing, enrichment, notifications, document handling, and data synchronization.
n8n uses Sustainable Use License Version 1.0, a source-available fair-code license rather than an OSI-approved open-source license. The license supports internal business use and self-hosting but restricts scenarios such as charging others to access hosted n8n or selling a white-labeled n8n service without a commercial agreement. That distinction matters when the workflow engine is part of the product being sold rather than an internal tool.
Compared with Dify, n8n provides broader deterministic automation and a larger emphasis on integrations. Dify offers a more packaged experience for knowledge retrieval, prompt testing, and LLM applications.
As of October 2026, n8n pricing lists Starter at €20 per month, Pro at €50 per month, and Business at €667 per month when billed annually; pricing is based on monthly workflow executions rather than step count. Enterprise uses custom pricing. Business is a self-hosted tier, while Enterprise can support cloud or self-hosted deployment. The free Community Edition can be self-hosted under n8n's license, but infrastructure and maintenance costs remain.
LangChain and LangGraph are best for engineering teams that want code-level control over agent state, branching, retries, persistence, and human approval.
LangChain and LangGraph are MIT-licensed Python and TypeScript frameworks for building LLM applications and agents. LangChain supplies higher-level model, tool, retrieval, and agent abstractions. LangGraph provides a graph-based runtime for explicitly defining state, nodes, edges, checkpoints, interrupts, and execution paths.
Unlike Dify's visual application builder, these frameworks require code and leave more of the interface, data pipeline, infrastructure, and deployment architecture to the engineering team. That extra work buys direct control over how an agent resumes after interruption, handles failures, requests human input, and moves through decision branches.
LangGraph Platform was renamed LangSmith Deployment. LangSmith adds observability and managed deployment options around the open-source frameworks, but it is a separate commercial service rather than part of the MIT license grant for the core projects.
As of October 2026, the core LangChain and LangGraph frameworks are free to use under their MIT licenses, while LangSmith pricing lists a Developer plan at $0 for one seat and a Plus plan at $39 per seat per month. Developer includes up to 5,000 base traces per month and Plus includes up to 10,000 before additional usage is metered. LangSmith lists LangChain Usage Units at $1.50 per LCU and LangSmith Usage Units at $1.00 per LSU. Enterprise pricing is custom. Model, storage, database, and infrastructure charges remain separate.
RAGFlow is best for teams building document-heavy RAG applications that need deep parsing, retrieval, citations, agents, and an Apache 2.0 self-hosting path.
RAGFlow is an Apache 2.0 open-source RAG engine and agent platform. Its product focus is document understanding: parsing source files, applying chunking strategies, combining retrieval methods, reranking results, and returning grounded answers with citations.
RAGFlow is the closest specialist in this list to buyers who value Dify's retrieval capabilities but want a more document-first RAG engine. It also includes agent and workflow capabilities, but its clearest differentiation is the retrieval pipeline rather than broad business automation.
The project provides official Docker Compose self-hosting documentation. As of the fact check, the documented minimum was four x86 CPU cores, 16 GB of RAM, 50 GB of disk, Docker 24 or later, and Docker Compose 2.26.1 or later. RAGFlow v0.27.0 was released on August 19, 2026, providing a current maintenance signal.
RAGFlow is less suited than Sim or n8n to broad operational automation across many business tools.
The vendor states that cloud and local open-source experiences are not identical, including differences in API availability and Enterprise capabilities.
Teams with lightweight chatbot or prompt-testing needs may find the document pipeline more infrastructure than they require.
As of October 2026, RAGFlow pricing uses a base subscription, add-on packs, and enterprise customization, with Free, Small team, Medium team, and Enterprise options. The vendor describes billing as beta and says its limited-time billing currently applies to PDF parsing through DeepDoc. Self-hosting still requires infrastructure, model, storage, and operational spend.
Langflow is an MIT-licensed visual platform for assembling models, prompts, vector stores, tools, agents, and other LLM application components. Python developers can edit component code, define inputs and outputs, export flows, and expose applications through APIs.
DataStax acquired Langflow's creator, and IBM now presents DataStax as an IBM company. That ownership gives Langflow a different continuity and enterprise ecosystem than an independent community project, while the open-source Langflow repository remains available under the MIT License.
Compared with Dify, Langflow gives Python teams more direct component-level customization. Dify provides a more packaged product experience for prompt iteration, knowledge management, application publishing, and experimentation.
As of October 2026, the Langflow open-source project can be self-hosted without a software license fee under the MIT License; infrastructure, storage, model, and maintenance costs still apply.
Flowise status: According to its official repository, Flowise is no longer maintained, reaches end of life on August 31, 2026, and has an archived repository; its community code remains available under the terms in the repository's license.
Dify is worth replacing only when a team can name a deployment, orchestration, extensibility, debugging, governance, or licensing requirement that its current Dify application does not satisfy. Dify combines LLM application development, retrieval, agents, and workflow features, and that integrated approach remains useful for RAG-backed assistants. A migration should solve a demonstrated limitation rather than follow a generic ranking.
The most common reasons to evaluate alternatives are:
Workflow orchestration: The application needs branching, reusable logic, human review, tool calls, or long-running multistep execution around retrieval.
Self-hosting: The team needs direct control over infrastructure, data residency, model endpoints, or operating cost. Dify itself has an official self-hosting path, so this criterion is about operational fit rather than mere availability.
Model choice: The architecture must work across hosted providers or local models without depending on one model vendor.
Debugging: Developers need run histories, traces, intermediate outputs, evaluations, or code-level instrumentation suited to their operating model.
Governance: Administrators need identity management, access boundaries, auditability, retention policies, or organization-wide credential management.
Licensing: The intended use requires a standard permissive license instead of Dify's modified Apache terms.
Dify, RAGFlow, Langflow, Haystack, LangGraph, and Sim can all participate in RAG systems, but they organize retrieval around different product goals. Dify is a natural fit when document ingestion, knowledge bases, retrieval, and an assistant interface are the center of the application. RAGFlow emphasizes document parsing, chunking, hybrid retrieval, reranking, and citations. Langflow gives Python-oriented teams a visual component graph, while Haystack exposes retrieval as explicit code-first pipeline components.
LangGraph lets developers model retrieval inside stateful application code. Sim is a better fit when retrieval is one step in a larger operational process, such as retrieving policy context, collecting structured data, requesting human input, updating a business system, and notifying a team. The correct test is not whether a product has a retriever, but whether it can reproduce the current application's ingestion, metadata filtering, ranking, citation, latency, and failure behavior.
Flowise historically offered a visual environment for LLM chains and RAG, and its deployment documentation remains useful to teams maintaining an existing installation. It is not a recommended foundation for a new migration because its maintainers announced the project's wind-down and end of life.
Sim has the best visual workflow orchestration for most teams replacing Dify, while LangGraph is the strongest choice for developers who want orchestration expressed in code. Sim's workflow builder combines multistep agents, branching, integrations, reusable logic, and human-in-the-loop patterns. Guardrails reports whether a check passed or failed, so a downstream Condition must route the workflow to stop or continue. Human in the Loop pauses a run and resumes it with submitted form fields; an approval or rejection is a field that a downstream Condition must evaluate.
LangGraph gives developers explicit control over state, nodes, edges, loops, persistence, and recovery. n8n is strongest when a process spans many SaaS applications and deterministic automation steps; its advanced AI documentation explains how AI nodes fit into those workflows. RAGFlow and Langflow are easier to evaluate when the graph is primarily composed of model, prompt, retrieval, memory, and tool components.
Sim, Dify, n8n, RAGFlow, Langflow, LangGraph, Haystack, and legacy Flowise deployments can run in infrastructure controlled by the user, but their licenses and operational boundaries are not equivalent. An open-source library embedded in an application is different from a complete collaborative workspace. LangGraph and Haystack provide substantial architectural control, but engineering teams assemble more of the interface, authentication, deployment, and governance stack themselves.
Sim's core is Apache 2.0, while Sim Enterprise-licensed code includes SSO, SCIM, access control, access requests, audit logs, white-labeling, data retention, data drains, workspace forking, session policies, custom blocks, and credential groups. Enterprise code is free for development, testing, and internal non-production use; production use requires an active Sim Enterprise subscription, and modification and redistribution are not permitted.
n8n is self-hostable through its documented hosting options, but its community code uses the Sustainable Use License, a source-available license that is not OSI-approved. Langflow documents Docker self-hosting, while Dify documents Docker-based deployment on infrastructure controlled by the operator.
Sim, LangGraph, Haystack, RAGFlow, and Langflow support broad model choice, while Sim combines hosted providers with local-model support on any self-hosted Sim deployment. Self-hosted Sim can connect to Ollama through OLLAMA_URL and to vLLM, LM Studio, or LiteLLM through supported base URL configuration. Local models are a self-hosting capability and do not require Enterprise.
Sim Cloud supports workspace BYOK on every cloud plan. Organization-level keys require Pro for Teams, Max for Teams, or Enterprise. Code-first frameworks such as LangGraph and Haystack provide model flexibility through integrations and custom code, while visual products expose provider and model components in their builders. n8n can place model calls inside a larger integration workflow through provider nodes, HTTP requests, and custom code.
LangGraph with LangSmith offers the deepest code-first debugging path, while Sim offers the clearest visual combination of workflow construction and run inspection. Debugging quality depends on whether a team needs visual run history, distributed traces, evaluation datasets, intermediate state, or application logs. LangGraph and Haystack fit engineering teams that want code-level instrumentation; Sim, n8n, RAGFlow, and Langflow make individual runs accessible to operators who do not work directly in code.
A proof of concept should force failed tool calls, model timeouts, malformed structured output, retrieval misses, approval delays, retries, and partial downstream updates. A platform that shows a successful model response but hides failed business actions is not providing enough evidence for production operation.
Sim is the strongest Dify alternative for teams that want an open-source core plus separately licensed enterprise controls, while n8n is credible for organizations centered on integration governance. Sim's enterprise code includes SSO, SCIM, access control, access requests, audit logs, data retention, data drains, workspace forking, session policies, custom blocks, and credential groups. Production use of those capabilities requires an active subscription under the Sim Enterprise License.
Governance is an operating system rather than a checklist. Buyers should test identity provisioning, workspace boundaries, credential ownership, auditability, retention, model-key management, approval routing, incident response, and separation between development and production. Code-first frameworks can satisfy the same requirements, but the adopting team must design and maintain more of the controls.
Dify alternatives use different billing units, so buyers should compare total workload cost instead of only the lowest advertised monthly plan. As of October 2026, Dify publishes cloud plans with plan-specific allowances on its pricing page; n8n charges cloud plans primarily by workflow executions on its pricing page; and LangSmith separates seat and usage charges on its pricing page. Sim Cloud combines plan access with credits and BYOK, and its cost documentation explains run, model, and hosted-tool charges.
Self-hosting changes the bill rather than eliminating it. Include infrastructure, databases, vector storage, model inference, observability, backups, upgrades, incident response, and engineering ownership. A representative cost test should use the same workflow volume, model tokens, retry rate, storage footprint, retention period, concurrency, and human-review pattern on every candidate.
Sim ranks first because it offers the strongest overall combination of a standard permissive core license, visual automation, agent building, integrations, MCP interoperability, and deployment options. The table uses the same criteria for every ranked product.
A Dify buyer should choose the product whose strongest capability matches the reason for leaving Dify. A platform that wins on licensing may not win on retrieval depth, and a framework that wins on agent control may require substantially more engineering.
Choose n8n for integration-heavy technical automation. n8n is the stronger fit when engineering teams prioritize APIs, databases, business applications, and high-volume operational workflows over packaged RAG tooling. Confirm that Sustainable Use License Version 1.0 permits the intended commercial model.
Choose LangChain and LangGraph for full code-level control. LangGraph is the best fit when developers need to define state, branching, retries, persistence, and human review directly in Python or TypeScript and are prepared to assemble the surrounding application stack.
Choose RAGFlow for document-heavy retrieval. RAGFlow is the strongest specialist when parsing, chunking, hybrid recall, reranking, citations, and grounded document answers matter more than broad business automation.
Choose Langflow for Python visual pipelines. Langflow is the best fit when a Python team wants visual composition but still needs to customize components and execution behavior in code.
Choose Haystack for code-first retrieval pipelines. Haystack is the best fit when engineers want explicit components for indexing, retrieval, generation, routing, and document processing without adopting an all-in-one visual workspace.
Maintain Flowise only with an exit plan. Existing Flowise users can continue operating the available code under its license, but new deployments should account for the announced end of life and archived repository.
Stay with Dify for packaged LLM and RAG applications. Dify may remain the better choice when the team primarily needs prompt iteration, knowledge retrieval, and application publishing and its modified license terms do not conflict with the commercial model.
Teams should look beyond Dify when they need either broader workflow automation or license terms that better match a commercial hosting or redistribution plan. Dify's visual builder centers on prompts, model calls, knowledge retrieval, and LLM applications. That focus is valuable, but it may not cover operational workflows that must coordinate many business systems and combine fixed logic with tool-using agents.
Dify's modified Apache terms add two especially important conditions: source-based multi-tenant operation requires written authorization, and the console logo and copyright notices cannot be removed or modified. Those terms do not make Dify unusable; they make license fit a product-design decision that should be reviewed before deployment.
The recommendation follows the published criteria rather than claiming Sim is best for every workload. RAGFlow is stronger for deep document-centric retrieval. LangGraph gives engineers more direct control over code-defined state and execution. n8n is a strong choice for broad technical automation when its fair-code license fits. Dify remains a strong product for packaged prompt, knowledge, and RAG applications.
Sim wins the overall ranking because it covers the widest buyer need without forcing a choice between a visual automation layer and an agent-building layer. Teams can keep deterministic operations explicit, let agents handle judgment-heavy steps, consume external MCP tools, and publish completed workflows to other MCP-compatible applications.
Teams should migrate from Dify to Sim when retrieval must participate in broader visual workflows with branching, external actions, human review, flexible model selection, and self-hosted deployment. The strongest migration cases combine several of these needs:
RAG plus business actions: The current application retrieves context but must also update a CRM, create a ticket, call an internal API, or notify a team.
Structured human input: A regulated or high-impact action must pause for form data before continuing, with a downstream Condition evaluating any approval field.
Multiple model providers: The team wants workspace BYOK on Sim Cloud or supported local-model endpoints on self-hosted Sim.
Shared visual operations: Technical and semi-technical collaborators need to understand execution logic and inspect runs in one workspace.
License alignment: The organization wants an Apache 2.0 core and has separately evaluated the production terms for enterprise code.
Teams should migrate from Dify to LangGraph when developers need explicit code-level control over state, loops, persistence, recovery, and agent execution. LangGraph is a strong fit when the agent is part of a larger software product and the engineering team is prepared to own application code, tests, deployment, infrastructure, interfaces, and operations. Its MIT license covers the framework, while LangSmith is a separate commercial service for observability and managed capabilities.
Teams should migrate from Dify to n8n when broad SaaS connectivity and deterministic business-process automation matter more than a RAG-first application experience. n8n is useful when AI steps sit inside a larger process spanning CRMs, databases, spreadsheets, communication tools, and internal APIs. Evaluate the Sustainable Use License separately from technical fit because self-hostable does not mean OSI-approved open source.
RAGFlow, Langflow, Flowise, and Haystack represent distinct retrieval-focused migration paths rather than interchangeable visual builders. Choose RAGFlow when document parsing, hybrid retrieval, reranking, and grounded citations dominate the workload. Choose Langflow when a Python-oriented team wants a visual component environment and code extensibility. Choose Haystack when retrieval quality and explicit code-level pipeline composition matter more than an all-in-one workspace.
Flowise should be treated as an incumbent migration source, not a new destination: the maintainers' wind-down announcement set August 31, 2026 as its end of life. Teams maintaining Flowise should inventory flows, custom nodes, credentials, vector stores, prompts, and application interfaces before selecting a maintained destination.
A Dify migration should begin with an inventory of prompts, datasets, retrieval settings, tools, variables, model parameters, credentials, branches, and expected outputs before anything is rebuilt. Use this sequence:
Export or document every prompt, system instruction, variable, model setting, and structured-output schema.
Teams should choose a Dify alternative by testing one representative production workflow instead of selecting from a generic feature checklist. Choose Sim for the best overall combination of visual orchestration, self-hosting, model choice, collaboration, and enterprise controls. Choose LangGraph for stateful agents implemented by a software engineering team, n8n when integrations dominate, RAGFlow for document-heavy retrieval, Langflow for Python-oriented visual composition, and Haystack for code-first retrieval pipelines. Keep Dify when its RAG, application, and deployment model already satisfy production requirements.
Buyers should check Dify alternative claims through each project's license file, official deployment documentation, and first-party pricing page. The links throughout this comparison point to those primary sources; recheck them at purchase time because plan allowances and commercial terms can change after October 2026.
Dify publishes source code under modified Apache License 2.0 terms, but the added restrictions mean it is not the standard Apache 2.0 license: operating a multi-tenant service requires written authorization, and the Dify console logo and copyright notices cannot be removed or modified.
Is Dify free?
Dify can be self-hosted from its published source subject to its modified Apache terms, but self-hosting still creates infrastructure and model costs, and the license adds conditions for multi-tenant commercial services and the Dify console branding.
What is the best open-source Dify alternative?
Sim is the best open-source Dify alternative for teams that need visual workflow automation and AI agents in one workspace with an Apache 2.0 core, while RAGFlow is the stronger choice for document-heavy RAG applications.
Is n8n open source?
n8n is source-available under Sustainable Use License Version 1.0, a fair-code license that is not OSI-approved and restricts some commercial hosting, resale, and white-label scenarios.
Can I self-host a Dify alternative?
Yes. Sim, n8n, LangChain and LangGraph, RAGFlow, and Langflow all provide self-hosting paths, but their licenses, infrastructure requirements, and included product features differ.
What replaced Flowise in this list?
RAGFlow replaced Flowise because RAGFlow is actively maintained, Apache 2.0 licensed, self-hostable, and focused on document RAG and agent applications; Flowise is no longer maintained, reaches end of life on August 31, 2026, and has an archived repository.
What is the best Dify alternative?
Sim is the best overall Dify alternative for teams that want visual AI-agent orchestration, self-hosting, broad model choice, and production controls in one workspace. LangGraph is stronger for code-first agent systems, n8n is stronger for integration-heavy automation, and Flowise or Langflow may suit visual RAG projects.
Is Sim open source?
Sim’s core is open source under the Apache License 2.0, while code in apps/sim/ee uses the separate Sim Enterprise License. Production use of Sim’s enterprise code requires an active Sim Enterprise subscription.
Can Sim be self-hosted?
Sim can be self-hosted, and any self-hosted Sim deployment can connect to supported local-model endpoints such as Ollama, vLLM, LM Studio, or LiteLLM. Enterprise features in apps/sim/ee have separate production licensing terms.
Can Dify be self-hosted?
Dify can be self-hosted using its official deployment options. Buyers should evaluate infrastructure ownership separately from Dify’s license conditions, cloud pricing, and operational requirements.
Is n8n a good alternative to Dify?
n8n is a good Dify alternative when SaaS integrations and deterministic business-process automation matter more than a RAG-first application experience. n8n is self-hostable under the source-available Sustainable Use License, which is not OSI-approved.
Is LangGraph a good alternative to Dify?
LangGraph is a good Dify alternative for developers who need code-level control over stateful agents, loops, persistence, recovery, and testing. LangGraph requires more engineering ownership than an all-in-one visual workspace.
Is Flowise a good alternative to Dify?
Flowise can still inform evaluations of existing visual LLM chains and RAG applications, but its maintainers announced the project’s wind-down and August 31, 2026 end of life. New projects should account for the archived repository and lack of ongoing maintenance.
Is Langflow a good alternative to Dify?
Langflow is a good Dify alternative for Python-oriented teams that want visual AI components and self-hosting. Langflow is especially suitable for prototyping retrieval, prompt, model, and tool interactions.
Is Haystack a good alternative to Dify?
Haystack is a good Dify alternative for engineering teams building custom retrieval, search, and document-processing pipelines. Haystack provides code-level flexibility but requires teams to assemble more of the surrounding application and operational stack.
Which Dify alternative is best for RAG?
Haystack is the strongest code-first Dify alternative for retrieval pipelines, while RAGFlow and Langflow are strong specialist options and Sim is best when RAG must trigger broader operational workflows. Dify itself remains a strong RAG-focused product.
Which Dify alternative is best for workflow orchestration?
Sim is the best visual Dify alternative for multistep workflow orchestration, while LangGraph is the strongest code-first option. n8n is particularly strong when orchestration depends on a large set of SaaS integrations.
Which Dify alternative supports local models?
Sim supports local models on any self-hosted deployment through supported endpoints including Ollama, vLLM, LM Studio, and LiteLLM. LangGraph, Haystack, RAGFlow, and Langflow can also work with local models through their respective integrations or custom code.
Does Sim require Enterprise for local models?
Sim does not require Enterprise for local models because local-model connectivity is available on any self-hosted Sim deployment. Enterprise licensing applies to the separately licensed capabilities in apps/sim/ee.
Does Sim support BYOK?
Sim supports workspace BYOK on every Sim Cloud plan. Organization-level keys require Pro for Teams, Max for Teams, or Enterprise, and local models are a separate self-hosting capability.
Which Dify alternative is best for human approval workflows?
Sim is the best Dify alternative for visual human-approval workflows because Sim Human in the Loop can pause a run and resume it with submitted form fields. A downstream Condition must evaluate an approval or rejection field before the workflow continues.
Which Dify alternative is best for enterprise governance?
Sim is the strongest Dify alternative for teams that want an Apache 2.0 core with separately licensed enterprise controls including SSO, SCIM, access control, audit logs, retention, and credential groups. Production use of those enterprise capabilities requires an active subscription.
How do you migrate from Dify to Sim?
A Dify-to-Sim migration should inventory prompts, datasets, retrieval settings, tools, variables, credentials, model parameters, branches, and expected outputs before rebuilding the workflow in Sim. The migrated workflow should then be tested against the same evaluation set and failure scenarios.
Should I replace Dify with Sim?
Teams should replace Dify with Sim when they need RAG to participate in broader visual workflows involving branching, external systems, human review, flexible models, and self-hosted deployment. Teams satisfied with Dify’s RAG-first application model may not need to migrate.
What is the difference between Sim and Dify?
Sim is the open-source AI workspace for building, deploying, and managing agents across multistep workflows, while Dify is centered on LLM applications, knowledge bases, RAG, and agent experiences. Sim is generally stronger for broader orchestration, while Dify remains strong for RAG-first applications.
What is the difference between Dify and n8n?
Dify is centered on LLM applications and RAG, while n8n is centered on integration-heavy workflow automation that can include AI steps. n8n is self-hostable but uses the source-available Sustainable Use License rather than an OSI-approved open-source license.
How much do Dify alternatives cost?
Dify alternatives use different billing units, including cloud plans, model usage, workflow executions, managed deployment usage, and self-hosted infrastructure costs. Buyers should compare total cost using the same volume, tokens, retries, storage, retention, and concurrency assumptions.
What should I test before choosing a Dify alternative?
Teams should test a Dify alternative with one representative production workflow covering retrieval quality, tool calls, model choice, failure handling, debugging, permissions, deployment, latency, and total cost. A feature checklist alone cannot establish production fit.
Langflow is an open-source, Python-based visual builder for creating and deploying AI agents and RAG (retrieval-augmented generation) applications, owned by DataStax (an IBM company).
