OpenMetadata Reviews & Product Details

OpenMetadata is the #1 open context layer for humans, AI assistants, and agents. It unifies technical context, business semantics, and organizational memory into one graph, so AI agents and humans reason from the same trusted foundation. Built by the founders of Apache Hadoop, Atlas, and Uber Databook, OpenMetadata unlocks the value of data assets with an open-source context layer that includes data cataloging, discovery, governance, data quality, observability, lineage, semantics, and memory for people and AI.

Seller

Collate

Discussions

OpenMetadata Community

Overview by

Shawn Gordon

Pricing

Pricing provided by OpenMetadata.

Open Source

Free

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User Insights

Average based on 5 real user reviews.

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OpenMetadata Integrations

(4)

Integration information sourced from real user reviews.

MJ

Marcio J.

CEO and Data Scientist

Computer Software

Small-Business (50 or fewer emp.)

9/13/2026

"All-in-One Open-Source Data GovernanceOpen source with an enterprise-grade feel with an Intuitive UI"

5/5

What do you like best about OpenMetadata?

It combines open-source technology with comprehensive, all-in-one governance capabilities—including a catalog, lineage, data quality, and a business glossary—eliminating the need to integrate multiple disparate tools. The product's pace of evolution is also a standout feature: capabilities like Data Contracts and the MCP Server demonstrate that the team is addressing real, current challenges rather than just maintaining the basics. The UI is intuitive enough for business teams to use without constantly relying on engineering. Review collected by and hosted on G2.com.

What do you dislike about OpenMetadata?

The main consideration is resource consumption for production; even in a basic setup, the server, database, and Elasticsearch/OpenSearch collectively require significant resources, necessitating infrastructure planning right from the start. Another factor is the pace of evolution: the project frequently releases new versions, and major changes—such as the recent migration of the ingestion engine to a new version of Airflow—demand extra care during upgrades, as poor planning carries a risk of breaking the system. Finally, the line between what is 100% open source and what steers users toward Collate’s commercial offering isn't always entirely clear, so it pays to know how to distinguish between the two from the outset. Review collected by and hosted on G2.com.

What problems is OpenMetadata solving and how is that benefiting you?

OpenMetadata solves the problem of metadata being scattered across different tools; previously, one had to hunt for information on lineage, quality, and ownership across separate systems, whereas now everything is centralized in a single catalog. This directly benefits our clients who need to demonstrate regulatory compliance (such as the Central Bank’s Joint Resolution 18): full traceability—tracking data from its origin through its journey to the parties responsible for it—shifts from a manual task to something that can be queried in minutes. It also addresses the issue of "governance in theory but not in practice"—features like Data Contracts and asset certification transform governance intentions into real, auditable processes, rather than just documentation in a PDF that no one follows. Review collected by and hosted on G2.com.

MA

Mohamed A.

IT System & Application Analyst

Mid-Market (51-1000 emp.)

9/25/2026

"API-First Governance That Fits Microsoft Fabric Seamlessly"

4/5

What do you like best about OpenMetadata?

We run most of our analytics on Microsoft Fabric, and honestly finding a governance tool that didn't fight the Fabric ecosystem was harder than expected. OpenMetadata's API-first approach made it possible to pull column-level lineage straight from Fabric pipelines without installing anything custom on the extraction side, which was a big deal for us since we didn't want another agent or connector adding overhead to production pipelines. The self-hosted deployment gave us full control, and the ingestion framework was flexible enough that we could catalog our lakehouse assets and start layering data contracts and quality checks as code on top without much friction. The part that's been genuinely useful beyond documentation is exposing that governance context through an MCP server, so an AI agent can actually query lineage and quality context instead of us guessing from table names. Review collected by and hosted on G2.com.

What do you dislike about OpenMetadata?

The learning curve on the ingestion framework config isn't small if you're doing anything beyond the standard connectors, we had to spend real time understanding the YAML structure and debugging a few ingestion pipeline failures before things ran cleanly. Documentation on advanced customization (custom connectors, MCP-specific setup) is thinner than the core product docs, so we ended up relying on community channels and trial and error more than I'd have liked. Also the UI can feel like it's doing a lot at once when you're onboarding new team members who haven't worked with a catalog tool before. Review collected by and hosted on G2.com.

What problems is OpenMetadata solving and how is that benefiting you?

We had zero visibility into lineage after migrating to Fabric, and no consistent way to enforce data quality or track it back to source when something broke. OpenMetadata gave us a single place for lineage, cataloging, contracts, and quality observability, and now that we're exposing it through MCP, it's also becoming the context layer our AI agents rely on instead of guessing from raw schema. That's cut down a lot of manual back-and-forth on "where did this number come from" and given us a real answer to data trust questions we couldn't answer before. Review collected by and hosted on G2.com.

RS

Rahul S.

Data Architect

Enterprise (> 1000 emp.)

9/21/2026

"Powerful Business Data catalog solution for large enterprise and AI readiness"

4/5

What do you like best about OpenMetadata?

I like the versatile architecture of OpenMetadata, which provides a robust foundation to handle our massive scale without creating bottlenecks. Its flexible design allows us to build custom connectors and define our own entity types, and we've even contributed a new connector to the community. Additionally, having an active user community is great, as it supports managing large user personas with continuous improvements. The performance on large installations is impressive, connecting seamlessly with various big data technologies like Salesforce and Snowflake. Also, the initial setup was easy. Review collected by and hosted on G2.com.

What do you dislike about OpenMetadata?

The governance report in OpenMetadata is very limited and doesn't solve most of the domain-level insights. It requires users to build their own integrations, which can be a hassle. I'd really like to see domain insights that clearly show metadata coverage and an observability report included. Having an overall score would make it easier for data consumers to use. Review collected by and hosted on G2.com.

What problems is OpenMetadata solving and how is that benefiting you?

I use OpenMetadata as our primary data catalog, solving data discovery and governance challenges. It supports a data mesh architecture, managing multiple domains and integrates with tools like Salesforce and Snowflake. It handles massive scale, supports thousands of users, and manages over half a million assets efficiently. Review collected by and hosted on G2.com.