Analytics & BI · Data & Analytics
Should you build or buy Data Catalog?
A data catalog is a metadata management system that indexes an organization's data assets — tables, columns, dashboards, pipelines, and ML models — and makes them searchable with business context, ownership information, and usage statistics. It solves the discoverability problem: helping analysts and engineers find the right dataset, understand what it means, and trust that it's current.
The build-vs-buy decision for Data Catalog turns on whether your catalog needs center on internal developer experience — where major tech companies built and open-sourced production solutions — or on business-user adoption and collaboration workflows where vendor onboarding programs and professional services add real value.
Build it, buy it, or bridge?
When building makes sense
The catalog problem is well-understood enough that major technology companies built their own solutions and then released them as open source. DataHub originated at LinkedIn and is now documented in production at thousands of organizations. Amundsen came from Lyft. OpenMetadata is a more recent entrant that 2026 buyer guides describe as production-ready for engineering-led teams. AI has also made one of the historically tedious parts of catalog maintenance — writing column descriptions and business context — substantially faster through LLM-assisted documentation generation. The build case earns its keep when catalog needs center on internal developer experience, when deep integration with your specific dbt models, Airflow DAGs, and warehouse tables matters more than a polished collaboration UI, and when you have a data platform team to run the catalog as part of the broader data infrastructure.
When buying makes sense
Buying from Alation, Atlan, or Informatica Data Catalog makes sense when the catalog's primary job is driving adoption across non-technical stakeholders rather than serving the engineering team's discoverability needs. Vendors have built onboarding programs specifically designed to solve the most common catalog failure mode: the tool gets deployed, engineering team loves it, and business users never start using it. Commercial platforms also provide collaboration features — annotations, certified datasets, data stewardship workflows — that are useful when business and data teams need a shared surface for data trust. If data catalog adoption is a visible organizational goal with executive sponsorship, the vendor's professional services and implementation support often justifies the contract.
The desk read
The catalog problem is well-understood enough that major tech companies built their own solutions and then open-sourced them. DataHub came from LinkedIn and runs at thousands of organizations today. Amundsen came from Lyft. Both are documented as production-ready, and the pattern of building on top of one of these engines rather than buying a managed vendor is now mainstream for engineering-heavy teams.
Buying from Alation or Informatica Data Catalog makes sense when you need the collaboration features, the managed infrastructure, and especially the professional services to drive adoption across non-technical stakeholders. Catalogs are notoriously hard to get used, and vendor onboarding programs exist to solve that. The build case earns its keep when your catalog needs are primarily internal developer experience, you have a data platform team to run it, and you'd rather own the search and discovery surface than be on a vendor's release schedule.
Frequently asked
What is a Data Catalog?
A data catalog is a metadata management system that indexes an organization's data assets — tables, columns, dashboards, pipelines — and makes them searchable with business context, ownership information, and usage statistics, solving the discoverability problem for analysts and engineers.
When does building a Data Catalog make sense?
Building makes sense when catalog needs center on internal developer experience, deep integration with your specific tooling stack matters, and you have a data platform team willing to run the catalog as infrastructure.
When does buying a Data Catalog make sense?
Buying earns its keep when driving adoption across non-technical stakeholders is the primary goal — vendors have built onboarding programs specifically designed to solve that adoption problem.
What are the main Data Catalog vendors?
Representative vendors include Collibra, Alation, Atlan, DataHub (LinkedIn). B4 Pro scores the full set.