Dify vs n8n: which fits your internal AI tools
Choose Dify when the internal AI tool is an LLM application built around prompts and knowledge, such as a document Q&A assistant or an agent that answers from your own content, and n8n when the main job is process automation that calls a model as one step among many systems. Dify is an LLM application development platform with a prompt IDE, RAG pipelines, agents and backend-as-a-service APIs. n8n is a workflow automation platform with more than 1,500 advertised integrations, where an AI node is one tool in a larger process. Four conditions decide it: whether the tool needs a user-facing interface, how many systems it must read from and write to, whether one internal unit uses it or several tenants do, and whether the license terms fit how you plan to use the code.
Ask first whether people will open the tool in a browser to chat with it. Dify ships a web app layer for published apps, so a knowledge assistant for a team usually stays inside Dify. If the output goes into a ticketing system, a CRM or a messaging channel and no one needs a dedicated front end, n8n's canvas and integration catalog usually fit better. Count the systems the workflow touches. A tool that mostly retrieves from a document store and calls one model suits Dify's built-in knowledge and vector store settings, while a tool that moves records across many SaaS applications suits n8n. Confirm each integration you need is available as a node in your n8n edition before you commit.
The license question is the one teams most often miss. Dify uses a modified Apache License 2.0 that prohibits operating a multi-tenant environment from its source without written authorization, and a tenant here means a workspace. The Community edition is limited to a single workspace, so an internal unit can run it, but a shared service for several business units or customers needs a commercial arrangement. n8n's Sustainable Use License permits use only for your own internal business purposes or non-commercial use, and files with .ee in their name or directory need an n8n Enterprise License. Internal use fits both, but a service you sell or offer to external parties does not fit n8n's terms. Have counsel confirm the license text against your intended use before you build.
Which platform fits which internal AI scenario
This table maps common internal AI scenarios to the platform that fits each one better, and names the condition that would change the answer. Read it as a starting point: most teams find their answer in the license terms and the number of tenants or identity requirements that apply to them.
| Scenario | Better fit | Why and what changes the answer |
|---|---|---|
| Internal knowledge assistant over company documents | Dify | Dify includes a RAG pipeline and app publishing in one product, so staff can query documents through a published app. n8n can call a model over documents, but you would assemble retrieval and the chat front end yourself. |
| Staff Q&A agent delivered as a chat app | Dify | Dify builds agents and publishes them as chat apps with a prompt IDE and backend APIs. If the chat is only a trigger for a back-end task, n8n's workflow model may be enough. |
| Process automation triggered by tickets or forms that calls an LLM step | n8n | n8n's visual canvas, custom JavaScript or Python code and catalog of more than 1,500 integrations suit event-driven processes. Choose Dify instead if the LLM step is the product and the workflow is secondary. |
| Multi-department AI portal inside one company | Depends on edition and license | Dify Community is limited to a single workspace, so several departments need Dify Enterprise or a different structure. n8n's Community edition is free for internal business use, but SSO and environments with Git need the Business or Enterprise plan. |
| Several business units served as separate tenants | Neither on Community | Dify's license forbids operating a multi-tenant environment from its source without written authorization, and Community is single-workspace. Confirm terms with LangGenius and n8n before building a shared service for separate units. |
| Company that needs SSO on the app layer | Dify Enterprise or n8n Business | Dify Enterprise lists OpenID Connect, SAML and OAuth2 with separate scopes for workspace and web app access. n8n SAML is included on Business and Enterprise plans, but it secures n8n itself rather than your published AI apps. |
| Company that will run the platform as a commercial service | Confirm with vendors | n8n's Sustainable Use License limits use to internal business or non-commercial purposes. Dify's license restricts multi-tenant operation and logo removal. Have counsel review both before selling access to customers. |
How Dify and n8n are built and what that means for operations
Dify and n8n both run as self-hosted services, but they put their moving parts in different places. Dify is a multi-container Docker Compose stack centered on RAG and LLM app state, while n8n separates trigger handling from execution once you move to queue mode. The cards below cover what each stack means for upgrades, backups and on-call work.
Dify's Docker Compose stack
The standard Dify deployment starts the api, worker, web, plugin daemon, PostgreSQL, Redis, Weaviate, Nginx, a code sandbox and an SSRF proxy. Each service is a separate failure point, so on-call staff need to know which container failed before restarting anything. Plan to back up PostgreSQL and the vector store together so chunks and metadata stay in step. Confirm the 2 CPU core and 4 GB RAM minimum against your expected app and knowledge load, and check Docker Compose 2.24.0 or later on the host.
Dify's security-sensitive settings
The SECRET_KEY signs session cookies and JWTs and encrypts OAuth credentials, and changing it after deployment logs out all users. Store it in your secrets manager before the first start, because a lost or rotated key affects every user session. The SSRF proxy blocks requests to internal and private IP ranges, so confirm that any internal model endpoint or data source you need is reachable through the proxy's rules. Upgrades that touch the sandbox or proxy should be tested first.
n8n queue mode topology
In queue mode, the main instance handles triggers and webhooks and passes executions through Redis to a pool of workers that read and write workflow data in PostgreSQL. Scaling means adding workers, but webhook traffic and the main instance remain a single point you must watch. Size Redis and PostgreSQL for the execution volume you expect, and confirm with n8n which high availability options your edition includes, since multi-main setup is limited to Enterprise self-hosted deployments.
Shared encryption key across n8n nodes
In queue mode, the main instance's encryption key must be shared with every worker and webhook processor so they can read credentials stored in the database. This makes key distribution part of every new node build and every rotation. Losing the key means stored credentials cannot be decrypted, so back it up separately from the database dump. Treat key rotation as a planned change that touches all n8n processes at once.
Upgrades and backups for both stacks
Dify ships minor releases roughly monthly, and each upgrade touches several containers that share PostgreSQL and Redis state. n8n also needs main and worker processes on the same version before you cut over. For both, take a consistent backup of the database, file storage and vector data before each upgrade, and rehearse a restore on a copy. Ask each vendor for its supported upgrade path and what changes in the database schema.
On-call load and what to ask
Dify's on-call work centers on container health, the sandbox and the vector store, while n8n's centers on queue depth, Redis availability and worker capacity. Give each on-call engineer a runbook that names the component, the log location and the restart order. Before signing a scope, ask your implementation partner who owns the vector store, the proxy rules and the encryption key rotation, since these are where incidents usually start.
What each license allows and what each edition adds
Dify is released under the Dify Open Source License, a modified Apache License 2.0. The base Apache terms are modified in two places that matter for internal tools. First, the source code may not be used to operate a multi-tenant environment, where one tenant is one workspace, without written authorization from the licensor. Second, the logo and copyright information in the Dify console may not be removed or modified without authorization. The free self-hosted Community edition is limited to a single workspace. Dify Enterprise adds SSO, multiple workspaces, advanced security, a commercial license and professional support, and its pricing is custom.
- Single workspace on Community: an internal team that stays within one workspace can run the Community edition without an additional fee.
- Multi-tenant use: running one Dify instance that hosts several separated workspaces for different business units or customers falls under the authorization requirement.
- Console branding: changing the logo or copyright in the console needs authorization, so plan branding before rollout.
- Enterprise inclusions: SSO, multiple workspaces, advanced security, a commercial license and professional support are listed as Enterprise features.
- Quote scope: ask the vendor which of these terms apply to your deployment model and what a written authorization covers.
Confirm with the vendor and your counsel whether a planned department split needs more than one workspace, since that determines whether Community is enough.
n8n is distributed under the Sustainable Use License. It allows use or modification only for your own internal business purposes or for non-commercial or personal use, and distribution only free of charge for non-commercial purposes. Files with .ee in their name or directory are not covered by that license and need a valid n8n Enterprise License. The free self-hosted Community edition is available. SSO and LDAP, environments with Git, and log streaming are included only on the Business and Enterprise plans. The Business plan is listed at 667 euros per month billed annually and is currently self-hosted only. Enterprise pricing is custom and adds dedicated support with an SLA.
- Internal use: running workflows for your own staff matches the permitted purpose, but offering n8n-based services to outside customers may not.
- Enterprise code: any
.eedirectory requires a valid Enterprise License even when the rest of the codebase is used internally. - SSO and LDAP: these sit on Business and Enterprise, so Community deployments authenticate through other means.
- SAML: SAML single sign-on is available on Business and Enterprise, with setup guides for Okta Workforce Identity and Azure AD.
- Multi-main high availability: this is restricted to Enterprise self-hosted deployments.
Confirm which plan includes the identity and environment controls you need before choosing a tier.
Both products are source-available or open-core in ways that separate internal use from commercial distribution, but the boundaries differ. Dify's restrictions focus on multi-tenant operation and console branding, while n8n's focus on the purpose of use and on specific enterprise-licensed directories. For an internal AI tool used by your own employees, both licenses generally permit self-hosting, yet the paid features you need for identity, governance and support usually sit in the commercial tier. Plan the edition around those requirements, not around the free download.
- Internal versus customer-facing: if the tool will serve external customers or affiliates, review the terms on each side before building.
- Identity requirements: SSO and directory integration are paid features on both sides, so price them into the plan from the start.
- Support obligations: Enterprise tiers on both products include professional or dedicated support, which matters if the platform is business critical.
- Pricing transparency: Dify Enterprise is custom priced, and n8n Enterprise is custom priced, so request written quotes that match your scope.
- Counsel review: have counsel review each license against your intended use, user population and any hosting by third parties.
This is not legal advice. Treat the license texts as the controlling documents and confirm each point in writing with the vendor.
Dify vs n8n on the features that decide the choice
This table sets Dify's LLM app and RAG capabilities against n8n's workflow automation strengths, row by row. Read it by first asking whether your core need is AI apps with retrieval or automation across many business systems, then check the license and edition rows against how your team will use the software.
| Capability | Dify | n8n |
|---|---|---|
| Primary purpose | LLM application development platform for AI workflows, RAG pipelines and agents through a visual interface | Fair-code workflow automation platform combining a visual canvas with custom JavaScript or Python code |
| RAG and vector store options | Vector store defaults to Weaviate, with options including Qdrant, Milvus, pgvector, OpenSearch and Elasticsearch | No built-in RAG vector store is supplied in our research; confirm retrieval options with n8n before relying on them |
| Agent and LLM app publishing | Builds and publishes agents and LLM apps with a prompt IDE and backend-as-a-service APIs | Supports AI-driven workflows on the canvas; confirm agent and app publishing features against your version |
| Integration breadth | Supports many model providers; confirm connector coverage for your business systems | Advertises more than 1,500 integrations, and all plans include every integration |
| Custom code | Built around prompts, workflows and model configuration; confirm code node options in your version | Combines the visual canvas with custom JavaScript or Python code |
| Self-hosted database options | Metadata database can be PostgreSQL (default), MySQL or OceanBase | Queue mode stores workflow data in PostgreSQL; confirm other supported databases with n8n |
| High availability | Enterprise can be deployed on Kubernetes for high availability; Community runs anywhere Docker runs | Multi-main high availability is limited to Enterprise self-hosted, not Community or Cloud |
| SSO and SAML | SSO with OpenID Connect, SAML and OAuth2 is an Enterprise edition feature | SAML SSO is available on Business and Enterprise plans, not Community |
| Workspaces or tenancy | Community is limited to a single workspace; multiple workspaces are part of Enterprise | Unlimited users and workflows on all plans; confirm tenant separation needs with n8n |
| Release cadence | Dify 1.17.1 released September 10, 2026, with minor releases roughly monthly | n8n 2.43.7 published October 16, 2026 as the stable release |
| License for internal use | Modified Apache 2.0; multi-tenant operation and console logo or copyright removal require a commercial license | Sustainable Use License permits internal business or non-commercial use; .ee files need an Enterprise License |
How SSO and access control differ on the app layer and the workflow layer
Identity needs differ by what you are securing. In Dify, the question is who reaches a published app, who builds and edits apps in the console, and who holds the workspace. In n8n, the question is who edits workflows, who can see and reuse stored credentials, and which processes can decrypt them. Settle those three questions before comparing login options, because single sign-on alone does not answer any of them. On the Dify side, the Enterprise SSO documentation lists OpenID Connect, SAML and OAuth2, with identity providers such as Microsoft Entra ID, Okta and GitHub. It also separates SSO scopes for workspace access and web app access, so a user can be allowed into the console without automatically reaching every published app, or the reverse. Confirm which scope your identity provider configuration maps to each group. Also note that the Community edition is limited to a single workspace, so multi-workspace separation is an Enterprise decision.
Dify's SECRET_KEY is a different kind of control. The environment reference says it signs session cookies and JWTs and encrypts OAuth credentials, and changing it after deployment logs out all users. Treat it as a planned change with a maintenance window, and store it in your secrets manager rather than in an ad hoc .env file. Dify can also keep workspace encryption keys locally or in Azure Key Vault, which is a decision to make before you load production credentials.
n8n places its login controls on the Business and Enterprise plans, where SAML single sign-on has setup guides for Okta Workforce Identity and Azure AD, and LDAP is included on the same plans. The sharper risk is the encryption key. In queue mode, the main instance's encryption key must be shared with every worker and webhook processor so they can read stored credentials. Any process that holds that key can decrypt the credential store, so restrict who can reach worker hosts and plan key rotation with the same care as Dify's SECRET_KEY.
Before you choose, build a short access map. List the users who reach each published app, the users who edit workflows, and the systems that hold each credential, then mark which of those can be enforced by SSO and which depend on key handling. A team that only needs internal users to run an approved chat app may be well served by Dify's app-level scopes, while a team that lets analysts build automations against production systems needs n8n's edit controls and credential isolation checked first. Confirm each control against the current plan documentation and your own test tenant before you commit.
What drives the running cost of each platform
Neither platform's license fee is the largest line in most self-hosted budgets. The cards below cover what each stack needs to run, what a paid tier adds, the people time to operate and upgrade it, and the model and vector spend that sits outside both products. Ask every vendor and partner to price these items separately in the written scope.
Dify container footprint
A Docker Compose deployment starts the api, worker, web and plugin daemon alongside PostgreSQL, Redis, Weaviate, Nginx, a code sandbox and an SSRF proxy. The documented minimum is 2 CPU cores, 4 GB of RAM and Docker Compose 2.24.0 or later. Check whether your sizing covers the vector store and sandbox under load, not only the idle minimum, and budget the storage for uploaded knowledge files.
n8n workers and PostgreSQL
Queue mode splits the main instance from a pool of workers that read and write workflow data in PostgreSQL, with Redis passing executions between them. Worker count is the main scaling cost, and it grows with execution volume rather than user count. The shared encryption key must reach every worker and webhook processor, so plan how you store and rotate that key across the fleet.
Paid tier licensing
Dify's self-hosted Community edition is free but limited to a single workspace, and the Enterprise edition is custom priced and adds SSO, multiple workspaces and a commercial license. n8n's Community edition is free, while the Business plan is listed at 667 euros per month billed annually and is currently self-hosted only. Ask whether the license fee recurs annually, whether it covers the multi-tenant or internal-use conditions you need, and what happens at renewal.
Cloud plans as a baseline
n8n's Starter and Pro cloud plans are listed at 20 euros and 50 euros per month billed annually, and Dify Cloud Professional and Team are listed at 590 and 1,590 US dollars per year. Cloud removes the container and database operations but moves data outside your infrastructure and adds plan limits. Compare the cloud subscription against your self-hosting infrastructure and staff time before deciding, and confirm current prices on each vendor's pricing page.
Operating skills and upgrade cadence
Dify has shipped minor releases roughly monthly, with 1.16.0 on July 17, 2026, 1.17.0 on August 25, 2026 and 1.17.1 on September 10, 2026. n8n's stable line moves on its own cadence, with 2.43.7 published on October 16, 2026. Each upgrade needs a test environment, a database migration check and a review of release notes. Ask who on your team or partner's team owns that cycle and how many hours a month it consumes.
Model and vector spend outside both platforms
Model API charges and vector store hosting are paid to model providers, cloud vendors or database operators, not to Dify or n8n. Dify ships with Weaviate by default and can use Qdrant, Milvus or pgvector, and each choice adds its own storage and compute bill. Ask for token and storage estimates from your own usage, and confirm which provider contracts and data residency terms apply.
Support and quote checklist
Dify Enterprise includes professional support, and n8n Enterprise adds dedicated support with an SLA, but neither support tier is priced publicly in the supplied facts. Request a written quote that separates one-time setup and hardening from recurring license, support and upgrade work. Ask for the response windows, the named upgrade path, and what is excluded from the fixed fee.
How to move an app or workflow from one platform to the other
This sequence takes an internal AI tool from Dify to n8n, or the reverse, in an order that keeps the working copy live until the new one has been checked against the same inputs. It produces a documented inventory, a rebuilt and verified target, and a decommissioning record that states what data was kept and for how long.
Inventory prompts, knowledge bases and integrations
The team that owns the tool lists every prompt, model choice, knowledge base, tool call, webhook, scheduled trigger and downstream system the app touches. For Dify, this means the app's orchestration and knowledge settings. For n8n, it means each workflow's nodes, triggers and the systems they call. The output is a single inventory table with one row per component, marked as transferable configuration, rebuild, or retire. Ask both vendors, before the project starts, which export formats their current versions produce and whether those exports cover prompts, workflow definitions and credentials, since no migration tool is assumed here.
Map credentials, secrets and encryption keys
Credentials do not move as plain values. In n8n, stored credentials are encrypted with the instance's encryption key, and queue mode requires that key on every worker and webhook processor. In Dify, SECRET_KEY signs sessions and JWTs and encrypts OAuth credentials, and changing it logs out all users. The team records each external credential, re-issues it in the target platform under a named owner, and confirms which key material must be retained so older data stays readable during the parallel run. The check that closes this step is a list of every credential with its new location and owner, signed off by security.
Confirm the vector store and document path
If the tool uses retrieval, the team decides whether the target platform will read the same vector store or rebuild the index. Dify's default vector store is Weaviate, with options such as Qdrant, Milvus, pgvector, OpenSearch and Elasticsearch. n8n's retrieval depends on the nodes and vector store the team wires in, so the index is usually rebuilt from the source documents. The team confirms with each vendor whether embeddings can be exported and reused, and if not, reprocesses the source files. The check is a documented retrieval test set with expected source documents for representative questions.
Rebuild the logic that does not transfer
Dify's visual apps and n8n's node-based workflows model state, branching and tool use differently, so the team rebuilds those parts in the target instead of copying them across. Prompts move as text, but variable handling, agent tool selection and retry behavior are re-implemented and reviewed by the owner of the business process. Triggers are recreated and tested in a non-production environment with dummy payloads. The output is a target build that passes the same test cases as the source, with each deviation written down and accepted.
Re-create identity and access controls
Access must be rebuilt before users see the new tool. Dify Enterprise offers OpenID Connect, SAML and OAuth2 with separate SSO scopes for workspace access and web app access, while n8n SAML single sign-on is available on its Business and Enterprise plans. The team maps each existing role to a role in the target, checks which SSO options the chosen edition includes, and tests group membership with a pilot set of accounts. The check that closes this step is an access matrix comparing source and target roles, with each mismatch resolved or documented.
Run both platforms in parallel
The source app stays live as the system of record while the target receives the same test inputs and, where safe, a shadow copy of real requests. Outputs are compared on a fixed set of questions and workflow runs, with differences reviewed by the business owner and the security team. Usage, error and latency logs from both sides are kept so the team can see where behavior has changed. Parallel running ends when the owner signs off that the target meets the agreed test criteria for the full set of cases, not just a sample.
Cut over users and triggers
Cutover happens in a planned change window with a written rollback procedure. The team switches user links, webhook URLs and scheduled triggers in a defined order, disables the source triggers first so nothing runs twice, and confirms that the target receives every event. Support staff get the new entry point and known differences. The check that closes this step is a cutover record showing each trigger switched, the time it changed, and the first successful production run on the target.
Decommission the source with a retention record
After a stable period agreed by the owners, the source app or workflow is disabled, its credentials revoked, and its data handled under the retention rules the organization already applies to AI prompts, logs and documents. The team decides what to export for records, such as prompt versions, run logs and knowledge base contents, and where it is stored. The closing artifact is a decommissioning record that lists what was removed, what was retained, where, and who approved it, so auditors and future owners can trace the change.
Where internal AI tool projects usually run long
Projects on both platforms slip for different reasons, and the slips tend to appear after the first working demo. On Dify, the first risk is model provider setup: each provider's keys, endpoints and quotas must be configured and tested before anyone builds on them, and the team should confirm which models are approved for internal data. The second is knowledge ingestion. Chunking quality decides whether retrieval answers are useful, so plan time to test chunk sizes against real documents rather than accepting defaults. The vector store is the third decision. Weaviate is the default, and the environment reference lists Qdrant, Milvus, pgvector, OpenSearch and Elasticsearch as options, so pick one before loading data, because migrating a populated index is rework. Agent tools also need the sandbox and SSRF_PROXY settings reviewed, since the proxy blocks internal and private IP ranges and an agent calling an internal system may fail until the route is allowed deliberately.
The Community versus Enterprise decision belongs before go-live, not after. The Community edition is limited to a single workspace, and SSO, multiple workspaces and advanced security sit in the Enterprise edition, so a team that needs SSO or a second workspace will change its deployment plan later. Confirm the license conditions on multi-tenant use and console branding with the vendor before building a shared service for several departments. On n8n, the early risk is credential handling. Credentials are stored encrypted in the database, and in queue mode the main instance's encryption key must be shared with every worker and webhook processor. Missing or mismatched keys cause failures that look like broken integrations. Queue mode also needs worker sizing based on your execution volume, with Redis and PostgreSQL capacity planned alongside it.
Integration work is the largest variable on n8n. Each external system needs its own credential design, error handling and test data, and the number of nodes does not predict the effort. Plan for these tasks with named owners. Your team should own access reviews, deciding which users and service accounts can reach each system, and every data decision, including what documents, tickets or customer records may enter a model or workflow. DeployOpen works from a written, fixed scope, with deliverables and timelines agreed before work starts, so ask any implementer to list the integrations, environments and reviews included before signing. Ask for the same list in any quote, because a vague scope is the most common reason these projects run long.
Questions buyers ask before choosing Dify or n8n
Can Dify Community serve several departments or only one workspace?
The free Community edition of Dify is limited to a single workspace, so one Community install serves one workspace. Serving several departments as separate tenants is where the license matters: the Dify Open Source License forbids using the source code to operate a multi-tenant environment without written authorization, and one tenant is one workspace. Multiple workspaces are part of Dify Enterprise, which is custom priced and also adds SSO, advanced security, a commercial license and professional support. Ask Dify how the Community edition handles access between teams that would share one workspace, and get the Enterprise quote before you plan a multi-department rollout.
Does n8n's Sustainable Use License allow an internal AI tool used company-wide?
Probably yes for purely internal use, but confirm the scope with your counsel. The Sustainable Use License permits use or modification only for your own internal business purposes or for non-commercial or personal use. An internal AI assistant used by employees across the company fits internal business purposes. The license does not allow distribution free of charge except for non-commercial purposes, so serving customers, partners or contractors outside your organization, or embedding the tool in a product you sell, takes you outside that grant. Files with .ee in the name or directory need a valid n8n Enterprise License, so check whether any feature you depend on sits in those files. Read the current LICENSE.md before rollout.
How long does a first Dify or n8n deployment take, and what drives it?
No duration is supplied for this comparison, so ask for a timeline in the written scope and check its milestones against your own environment. The main drivers are the number and type of data sources and connectors, identity integration (SSO is a paid tier on both platforms), the model providers you use and whether they run inside your network, the choice of vector store and file storage, and the security review and testing your organization requires before go-live. Your team's experience with Docker, PostgreSQL and Redis also changes the schedule. Ask for dated milestones, the client dependencies behind each one and the acceptance criteria for sign-off.
Can our team run Dify or n8n without outside help?
A capable internal team can run either platform, but both need ongoing operations, and the work does not end at go-live. Dify's Docker Compose guide asks for at least 2 CPU cores, 4 GB of RAM and Docker Compose 2.24.0 or later, and starts PostgreSQL, Redis, Weaviate, Nginx, a code sandbox and an SSRF proxy alongside the api, worker, web and plugin daemon services. Dify's minor releases arrived roughly monthly in mid-2026, so upgrades recur. n8n queue mode needs PostgreSQL, Redis and the main instance's encryption key shared with every worker, and multi-main high availability is limited to Enterprise self-hosted deployments. DeployOpen can take on planning, implementation, upgrades and support under a written scope or a retainer, so you can decide which parts stay in-house.
What skills does each platform require from the engineering team?
Dify asks for container operations, PostgreSQL and Redis administration, and configuration of the vector store and file storage backends, plus prompt and retrieval design for the people who build apps. Its environment reference says that changing SECRET_KEY after deployment logs out all users, so whoever runs the platform needs to handle that secret carefully. n8n asks for workflow design on its visual canvas, JavaScript or Python for custom code, PostgreSQL and Redis for queue mode, and disciplined management of the encryption key that every worker needs. Builders on either platform need domain knowledge of the business process being automated. Map these skills to your team before you pick a platform, and note which ones you would have to hire or contract.
What does a fixed-scope implementation need from our side?
Most DeployOpen engagements are fixed-scope, with scope, deliverables and timelines agreed in writing before work starts, so your main job is to make decisions and provide access early. Typical inputs include access to the target cloud account, data center or air-gapped network, named owners for identity, data sources and sign-off, and decisions on the edition, model providers and vector store. Provide sample workflows or data sets for acceptance testing, and agree a change process for requirements added later, since they change the written scope. DeployOpen does not publish a price list, and a quote follows from the written scope, so the more precise your inputs, the more precise the quote.
Is single sign-on included free with Dify or n8n?
No. Neither platform includes SSO in its free tier. Dify's SSO is part of the custom-priced Dify Enterprise edition, which supports OpenID Connect, SAML and OAuth2 with identity providers such as Microsoft Entra ID, Okta and GitHub, and separate SSO scopes for workspace access and web app access. n8n's SAML single sign-on and LDAP are included only in the Business and Enterprise plans. The n8n pricing page lists the Business plan at 667 euros per month billed annually, and it is currently self-hosted only. Check that the tier you buy covers your identity provider's protocol, group mapping and access scopes before you commit.
What should we confirm in the license before signing?
Confirm how your intended use maps to each license before you sign. For Dify, confirm whether the deployment operates as a multi-tenant environment and whether the console logo and copyright will stay unchanged. For n8n, confirm that all users are internal, that nothing is distributed outside the company and whether any needed feature sits in .ee files. For both, confirm which edition includes SSO, workspace or user limits, support and any SLA, and the upgrade path, since minor releases arrive often. Get support terms and data handling written into the agreement. DeployOpen prepares systems, controls and evidence for compliance assessments, but independent auditors and certification bodies issue the reports and certifications.
How DeployOpen helps choose, implement or migrate Dify or n8n
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 n8n, we start by agreeing which internal AI tool or automation problem the platform must solve, then document the license conditions that apply to that use before any build begins.
How we scope
- Confirm the internal use case, user count and whether the deployment serves one workspace or several teams.
- Map the license conditions for Dify's modified Apache License 2.0 and n8n's Sustainable Use License to your intended use.
- Agree the written scope, deliverables and timelines in writing before work starts, with no prices in the scoping document.
- Identify which edition features your team needs, such as SSO, multiple workspaces or queue mode, so the quote matches them.
How we build
- Deploy the chosen platform in your own infrastructure, including the supporting databases, vector store and object storage it requires.
- Connect models, data sources and identity providers that your team has approved, and document each integration.
- Configure secrets and encryption keys, including handling of the Dify SECRET_KEY or the n8n encryption key shared across queue workers.
- Test outbound network controls, access paths and the sandboxing that applies to agents or code execution in your environment.
How we hand over
- Deliver architecture notes, configuration records and runbooks that your platform, security and compliance teams can review.
- Document the upgrade path for each platform, including how to track releases and test them before rollout in your environment.
- Walk your administrators through backup, restore and access management procedures, and record what each person owns.
- Provide evidence and control documentation for compliance assessments, noting that independent auditors issue any audit reports.
How we support
- Offer ongoing support, upgrades and continuous testing as a retainer after the initial handover is complete.
- Review new Dify and n8n releases against your configuration and license position before scheduling any upgrade.
- Re-test the platform after significant changes, such as new models, new integrations or a move between editions.
- Revisit the license and edition decision if your use changes, for example when internal tools reach external users.
