Open-source alternatives to Atlan: DataHub, OpenMetadata, Atlas

Which open-source alternative to Atlan fits your metadata residency needs

If your metadata has to stay inside your own infrastructure, DataHub and OpenMetadata are the two self-hosted catalogs to evaluate first, with Apache Atlas as the option to weigh if your estate is built around Hadoop. Teams usually start this search for one of three reasons: a renewal that reopens the question of where metadata lives, a residency rule that a vendor-hosted control plane does not satisfy, or a growing concern about how hard it would be to leave a single platform later. The underlying issue is architectural. Atlan describes itself as a cloud-first, single-tenant SaaS platform hosted on AWS, Azure or Google Cloud. For private sources, it offers a Self-Deployed Runtime that runs in your own network, but the core metadata platform still sits in Atlan's hosting model. Atlan's architecture documentation also states that the platform is built on Apache Atlas for metadata storage, with Cassandra and Elasticsearch, and uses Keycloak for SSO, OIDC and SAML. Before you decide, confirm with Atlan exactly which components would run in your account and which would not, and ask what your residency auditor will accept as evidence for each.

Start your evaluation by listing the metadata you cannot move out of your network: table and column names, lineage, glossary terms, classifications and access-related tags. Then map each item to the open-source option that would hold it. DataHub's open-source edition is Apache-2.0 licensed and can be started with the datahub docker quickstart command or deployed on Kubernetes. OpenMetadata is also Apache-2.0 licensed and documents production deployment on Kubernetes with Helm charts, on bare metal, or on managed Kubernetes services in AWS, Azure and Google Cloud. Confirm with each project which connectors your sources need and whether the features you rely on sit in the open-source edition or in the managed offering from the company behind it. Do not treat self-hosting as a cost-free exit. You will own upgrades, backups, access control, search and graph storage, and the on-call work that comes with them. Ask your platform team to estimate those components, and ask any implementation partner for a written, fixed scope that names the deliverables, the environments and the handover. Keep a dated record of this review, because it becomes the starting point for your residency evidence.

How DataHub, OpenMetadata and Apache Atlas compare for a self-hosted catalog

Three Apache-2.0 projects cover most self-hosted catalog needs, but they differ in age, deployment model and governance depth. Apache Atlas is also the metadata store that Atlan builds on, so it is the closest architectural relative of the product you are leaving. Use the cards below to shortlist options before you test them against your own sources.

DataHub for broad source coverage

DataHub is Apache-2.0 licensed and lists 150+ integrations, column-level lineage, governance and discovery in its repository. Teams that want to start quickly can run the Docker quickstart, then move to Kubernetes for production. The main trade-off is operational: you run the search, graph and ingestion components yourself, so confirm which of those your team can patch and monitor. Check whether the integrations you need are in the open-source edition or only in DataHub Cloud, which adds features such as access request workflows and compliance forms.

OpenMetadata for connector breadth and Helm

OpenMetadata is Apache-2.0 licensed, lists 130+ connectors and an OpenLineage connector, and exposes an MCP server for tooling that talks to the catalog. Its deployment documentation covers Helm charts on Amazon EKS, Azure AKS, Google GKE or on-premises Kubernetes, and bare metal, with Docker Compose for evaluation only. The trade-off is that governance workflows and connector maturity vary by source, so run a pilot against your slowest-moving system. Managed options and AI features come from Collate, which is a separate commercial choice.

Apache Atlas for Hadoop estates

Apache Atlas is an Apache-2.0 governance and metadata framework from the Apache Software Foundation, built for Hadoop. Its lineage, classification and Apache Ranger integration support classification-based access control, which matters if your policies already live in Ranger. Atlan itself stores metadata in Apache Atlas, so teams familiar with Atlan's internals will recognize the model. The trade-off is a narrower connector set and a more dated user experience than newer catalogs, so confirm the modern sources you need are supported before committing.

Choosing between the three

Pick DataHub when broad, current source coverage and column-level lineage matter most. Pick OpenMetadata when you want Kubernetes-native Helm deployment and an MCP interface. Pick Apache Atlas when Hadoop and Ranger-based classification access control are central to your estate. Whichever you choose, budget for the platform team that runs it, since the license is free but hosting, upgrades and support are not.

Which open-source option covers each Atlan capability

This table maps the main Atlan capabilities to DataHub, OpenMetadata and Apache Atlas, and marks where open source leaves gaps you must fill yourself. Read each row as a question to confirm against your own sources, identity provider and hosting model, since connector and SSO coverage depends on your environment.

Atlan capability	DataHub (open source)	OpenMetadata (open source)	Apache Atlas (open source)
Metadata discovery and search	Search and discovery across ingested assets, with 150+ integrations listed in the repository	Search and discovery across ingested assets, with 130+ connectors listed in the repository	Metadata catalog built mainly for Hadoop ecosystem sources; broader source coverage needs custom work
Column-level lineage	Supported in the open-source edition; confirm coverage for each of your engines	Lineage supported, including an OpenLineage connector; confirm column depth per source	Lineage supported, mainly for Hadoop-centric pipelines; confirm fit for your stack
Classification and governance	Governance and discovery included; compliance forms and access request workflows are DataHub Cloud features	Glossaries, tags and stewardship available; confirm role model against your policies	Classification and tagging, with Apache Ranger integration for classification-based access control
SSO with Keycloak (OIDC and SAML)	Supports OIDC and SAML configuration; confirm the exact setup with your identity provider	Supports OIDC-based SSO; confirm SAML needs and group mapping in your environment	Depends on the Atlas web and REST security setup; confirm SSO integration with your identity provider
Private-source connectivity	Self-hosted deployment reaches sources inside your network; no separate runtime component to manage	Self-hosted deployment reaches sources inside your network; confirm ingestion agent placement	Runs inside your network; connectivity to sources depends on the connectors you build or configure
Vendor-built connectors	Connectors maintained by the project community; confirm each connector version against your sources	Connectors maintained by the project community; confirm each connector version against your sources	Limited native source connectors; expect custom development for most non-Hadoop sources
Managed hosting and upgrades	Gap: DataHub Cloud is the managed option; self-hosting means your team or a partner runs upgrades	Gap: Collate offers managed OpenMetadata; self-hosting means your team or a partner runs upgrades	Gap: no managed offering from the Apache project; you own hosting and operations entirely
Uptime SLA and commercial support	Gap: the 99.5% uptime SLA applies to DataHub Cloud, not the open-source edition	Gap: commercial support and AI features come from Collate, not the open-source project	Gap: no commercial SLA from the Apache Software Foundation; support comes from your team or a partner

What you give up when you leave Atlan's managed service

Moving off Atlan's single-tenant SaaS trades vendor-run operations for work your team owns. The cards below cover the functions you stop receiving, and the usual ways teams replace each one, so you can price the gap before you commit.

Vendor-managed upgrades and uptime

Atlan's cloud platform is upgraded and kept running by the vendor. Self-hosted DataHub or OpenMetadata moves that work to your platform team, including version upgrades, database migrations, index maintenance and backups. DataHub Cloud, the managed product from the company behind DataHub, lists a 99.5% uptime SLA as a cloud-only feature. Ask any managed provider for its written uptime commitment, its maintenance windows and how upgrades are rolled out to your tenant.

Managed SSO and access

Atlan uses Keycloak for SSO, OIDC and SAML in its own stack. In a self-hosted catalog, you configure the identity provider, group mapping and role assignments yourself, and you own certificate rotation and offboarding. Confirm which SSO protocols each candidate supports in its current release, and whether it can map identity groups to catalog roles without manual edits.

Connector maintenance

Atlan maintains the connectors that sit between your warehouses and its metadata store. With DataHub or OpenMetadata, the connector libraries are open source, but upgrading a connector when a source system changes its API becomes your task. Inventory every source you ingest from, pin connector versions, and test ingestion in a staging environment before each platform upgrade.

Private connectivity to sources

Atlan's Self-Deployed Runtime runs inside your network to reach on-premises or VPC-locked sources. A self-hosted catalog runs wherever you deploy it, so network paths, firewall rules and secrets handling for each source become your responsibility. Document which sources need private routes, and confirm that the chosen deployment target can reach them without exposing credentials outside your perimeter.

Atlan-specific workflows and interface

Atlan's asset pages, workflows and stewardship features are its own design. Teams moving to DataHub or OpenMetadata must retrain users, rebuild saved views and re-create approval flows, such as access requests or certification steps. Map your current workflows before migration, and check which ones the target platform supports natively and which need custom development or a managed add-on.

Support response and runbooks

With Atlan, you open a support case with the vendor. After migration, incident response depends on your on-call team, community forums and any retainer you buy. Write runbooks for ingestion failures, search index problems and lineage gaps, and decide in advance whether you need a support retainer with a defined response commitment. Ask any provider to state its response targets in writing.

How to migrate metadata, lineage and access from Atlan

This sequence moves catalog metadata, lineage and access from Atlan's single-tenant SaaS into a self-hosted open-source catalog in steps that can be verified one at a time. Each step closes with a check, so the team knows when to move on and when to stop.

Inventory sources, connectors and assets
List every source system Atlan connects to, including the sources reached through the Self-Deployed Runtime, and mark which ones have a maintained connector in the candidate platform. Record asset counts per source, the custom metadata fields in use, and which lineage paths are manual or partial. Data engineering and the catalog owner should sign off the list. It is done when every source has a named owner and a connector status of supported, custom build or retire.
Export and map assets to the target model
Export asset inventory and relationships from Atlan through its API or export options, then map Atlan's types, attributes and custom metadata to the target catalog's entity model. Confirm the mapping for each asset type with the vendor documentation of the chosen platform, since DataHub and OpenMetadata model entities differently. Keep the exports in version control. It is done when a sample of each asset type loads in a test instance and its attributes match the source.
Migrate glossaries, domains and classifications
Move business glossary terms, domain or ownership structures and classification tags, and rebuild the mapping of Atlan tags to the target platform's tags or classifications. Stewardship roles and owner assignments need explicit mapping because the two platforms name and scope them differently. Agree the naming rules with the governance lead before loading. It is done when term counts, domain membership and owner assignments in the target match an agreed reconciliation report.
Rebuild lineage and validate depth
Recreate lineage from the source systems through the connectors of the target platform, not by copying lineage edges by hand. Compare lineage depth and column-level coverage for a set of critical tables against Atlan, and record every gap, especially for custom pipelines and manually curated links. Data engineers should own the gap list. It is done when each critical lineage path is either reproduced or listed as an accepted exception with an owner.
Pilot one domain end to end
Choose a single business domain with clear owners and a moderate number of sources, then run the full migration for that domain only. Users in that domain search, browse and review lineage in the new catalog and report differences. The pilot is complete when the domain owner signs off that discovery, ownership and lineage match what they used in Atlan. Use these findings to refine the mapping before wider rollout.
Run in parallel and cut over SSO and access
Run both catalogs side by side while metadata sync continues, then move authentication to the identity provider used by the target platform, such as OIDC or SAML through your existing directory. Map Atlan roles and access policies to the target's role model and test each group's permissions. Security and identity teams should verify that no user retains access they no longer need. It is done when a login and permission test passes for every role and the cutover is approved in writing.
Decommission Atlan and retain evidence
After the parallel period ends and the cutover is approved, disable Atlan connectors and users, confirm the agreed contractual steps for data return or deletion with Atlan, and archive the final exports and reconciliation reports. Keep the access change records for audit purposes. Confirm the retention requirements with your compliance team before deletion. It is done when Atlan access is removed, the archive is verified, and the decommission record is filed.

Which option fits your residency, cost or Hadoop situation

When metadata itself is regulated, for example because it describes personal data, customer schemas or sensitive pipelines, the catalog has to run where your data already sits. DataHub and OpenMetadata are both self-hosted in your own cloud account, data center or private network, and both can be deployed on Kubernetes. OpenMetadata documents production deployment with Helm charts on Amazon EKS, Azure AKS, Google GKE, on-premises Kubernetes, and on bare metal. DataHub can be started with the datahub docker quickstart command for evaluation and deployed on Kubernetes for production.

Best fit: DataHub on Kubernetes for teams that want broad connector coverage and column-level lineage inside their own network.
Best fit for bare metal: OpenMetadata, which documents a bare-metal option alongside Kubernetes.
Storage and search: Plan where the metadata store and search index live, since both sit inside your boundary and need backup.
Connectivity: Confirm how the catalog reaches sources that are locked to a VPC, because Atlan's Self-Deployed Runtime solved this in its own model and you will need an equivalent.

Confirm with the vendor which connectors your sources need and whether each one runs fully inside your network.

What moving off Atlan involves in cost, time and staff

How much effort does a migration off Atlan take and what drives it?

Effort depends mostly on how many metadata sources you connect, how much custom governance logic sits in Atlan today, and how many users must be retrained. Atlan is a single-tenant SaaS platform that runs on AWS, Azure or Google Cloud and can pair with a Self-Deployed Runtime for on-premises or VPC-locked sources, so the first step is an inventory of every connector, runtime and access path in use. Each source that needs a new connector, each custom classification and each workflow tied to Atlan's interface adds work. No duration is fixed here; ask any implementation partner for an estimate built from your own inventory and a written scope before work starts.

Can our team migrate off Atlan without outside help?

A team can do it in-house if it already runs data infrastructure and has time to absorb the project alongside daily work. The open-source options are real platforms with their own deployment paths: DataHub supports a Docker quickstart and Kubernetes, and OpenMetadata documents production Helm deployments on EKS, AKS, GKE, on-premises Kubernetes and bare metal. The harder part is usually ownership, not installation: someone must upgrade, back up and secure the stack after go-live. Outside help is most useful for fixed-scope work such as connector build-out, hardening and cutover, which can be agreed in writing before work starts.

What skills does a self-hosted catalog migration require?

The work needs platform engineers who can run Kubernetes or Docker-based services, data engineers who understand your source systems and their metadata APIs, and a security engineer who owns identity, network access and secrets. Governance staff are also needed to rebuild domains, ownership and classification rules in the new tool. Atlan's architecture documentation describes Apache Atlas for metadata storage, Cassandra and Elasticsearch, and Keycloak for SSO, so teams that already know those components will find parts of the stack familiar. Confirm the skill mix against the specific catalog you choose, since each project has its own dependencies and configuration model.

How do we export lineage and glossary content out of Atlan?

Start by confirming which export paths Atlan provides for your tenant and plan, because bulk export options differ by product and version. Treat lineage and glossary as separate workstreams: lineage is usually rebuilt by reconnecting sources to the new catalog, which re-harvests relationships, while glossary terms, owners and domains must be exported as structured content and mapped to the target's model. Keep a reconciliation sheet that records each term, its owner and its linked assets, then check counts after import. Ask the vendor and the target project which fields survive a round trip before you commit to a cutover date.

Can our existing identity provider replace Atlan's SSO?

In many cases yes, because both DataHub and OpenMetadata are designed to sit behind an enterprise identity provider, but the exact integration depends on the catalog version and deployment. Atlan's documentation states it uses Keycloak for SSO, OIDC and SAML, so the question for your team is whether your current provider supports the same protocols and group mapping you need for roles such as steward and admin. Confirm the supported SSO method, role mapping and session behavior in the target project's documentation, and test with a pilot group before moving all users.

How are upgrades and patches handled after a self-hosted catalog goes live?

Your team or a support partner takes on upgrades, patches, backups and monitoring, which Atlan currently carries for its SaaS customers. Release cadence matters: DataHub 1.7.0.1 was released on September 3, 2026, and OpenMetadata 2.0.5 was released on October 8, 2026, according to their GitHub release pages, so plan a regular review of release notes and a staging environment for each upgrade. Ask whether a retainer for ongoing support, upgrades and continuous testing fits your staffing, and agree in writing who handles incidents and rollback.

What recurring and one-time costs should we compare against Atlan?

Compare the one-time migration work with recurring infrastructure, staff time and support. On the self-hosted side the recurring items are compute and storage in your own cloud or data center, staff time for upgrades and monitoring, and any paid support or managed service you choose; for example, Collate offers managed OpenMetadata and DataHub Cloud is a separate managed product, each with its own pricing. On the Atlan side, the subscription is recurring. Request a quote built from your written scope that lists labor, infrastructure, licenses and support as separate lines, so the comparison holds up across several years.

What security checks should we run before cutting over to a self-hosted catalog?

Before cutover, confirm that the catalog's access model, secrets handling, network exposure and audit logging meet your policy, because metadata often reveals sensitive schema and lineage. Review the identity integration, restrict administrative roles, and run security testing against the APIs and web interface. Check that backups are encrypted and restorable, and document the evidence you will need for compliance assessments. DeployOpen can run security testing and prepare systems and evidence for compliance assessments, but it does not issue audit reports or certifications; independent auditors and certification bodies do that work.

What changes for your data team after the switch

The biggest day-to-day change is that your team will run the catalog's search, lineage and access controls itself, so the first decision is which open-source platform matches the way your analysts already work. DataHub and OpenMetadata both provide search and discovery across ingested sources, column-level lineage and ownership fields, but the screens, filter behavior and ranking will differ from Atlan. Atlas, by contrast, is oriented toward Hadoop-era type and entity models and typically needs more custom work to match a modern discovery experience. Run a pilot with a short list of real questions from analysts (for example, which table feeds a given dashboard) and time how long each platform takes to answer them, so the switch is judged on task results rather than feature checklists.

Stewardship and access control change the most for governance leads. Atlan's classification and policy model will not carry over as-is. Apache Atlas integrates with Apache Ranger for classification-based access control, which suits organizations that already run Ranger in Hadoop or similar stacks. DataHub and OpenMetadata use their own ownership, domain and role models, and you should confirm how each handles fine-grained row or column policies before assuming parity. Document every Atlan tag, owner rule and approval workflow, then decide which ones become catalog metadata, which become Ranger policies, and which need a custom workflow built and tested by your team.

Users also reach the catalog differently. Atlan's Slack and browser entry points, and any other vendor-hosted integrations, will need equivalents or should be dropped with users informed. Confirm which single sign-on method your identity provider supports for each candidate, since Atlan uses Keycloak for SSO, OIDC and SAML, and check whether the open-source edition or a supported add-on covers the same sign-on paths. Expect a period where analysts search in two places, so plan a cutover date, a redirect or bookmark plan, and a short training session on the new search and lineage views.

How DeployOpen scopes, migrates and supports a self-hosted catalog

DeployOpen plans, implements, customizes, integrates, hardens, backs up, upgrades, documents and supports self-hosted open-source platforms inside your own cloud accounts, data centers or air-gapped networks. For a move away from Atlan, we start with a written scope that fixes deliverables and timelines before any work begins.

How we scope

Written scope lists which sources, lineage paths and governance workflows the self-hosted catalog must cover
Engagements are fixed-scope, with deliverables and timelines agreed in writing before work starts
Scope records which Atlan-hosted components are replaced, including any Self-Deployed Runtime connections

How we build

Deploy DataHub or OpenMetadata in your infrastructure, using the deployment method your platform team has approved
Connect metadata sources, configure lineage ingestion and set up SSO through your existing identity provider
Test access controls, backups and upgrade paths, and document the results for your internal and audit reviews

How we hand over

Deliver architecture, runbooks and configuration documentation so your team can operate the catalog independently
Walk through backup, restore and upgrade procedures with the people who will run them after handover
Provide evidence of controls for your compliance assessors, noting that independent auditors issue any formal reports

How we support

Ongoing support, upgrades and continuous testing are available as retainers after handover
Retainers can cover version upgrades for the open-source platform you chose, scoped in writing
Ask any provider to confirm in writing which upgrade, patch and response commitments apply to your environment

Open-source alternatives to Atlan