Amundsen.
Founded 2019
Status · ● active
Verified · ● 6d ago
The Lyft-born OSS catalog that invented search-first discovery — historically important, but development has largely stalled since 2024.
Where it fits — and where it doesn't.
Teams that already run Amundsen and need to understand what they have, or teams with a genuinely minimal requirement — usage-ranked table search and ownership tracking, nothing more — who are comfortable owning a codebase that is no longer moving.
The core idea still holds up: index tables, dashboards, and people into Elasticsearch, rank results by query-log usage so the tables analysts actually trust float to the top, and keep the UX focused on the single question "which table should I use?" Databuilder's pull model is plain Python, so extending it from an existing Airflow deployment is straightforward for a data platform team.
You are choosing a catalog fresh in 2026 — the ecosystem has decisively moved to `datahub` and `openmetadata`, both of which cover Amundsen's discovery core plus glossary, governance, column-level lineage, and quality, with active communities.
Avoid also if you need any governance surface at all (glossary, PII classification, contracts, approval workflows — none exist), if you want a managed offering (Stemma is gone; no managed Amundsen exists), or if you can't staff the Neo4j + Elasticsearch + three-microservice operational footprint for software that won't be gaining features.
The honest scorecard.
- Pioneered usage-ranked, search-first discovery — PageRank-style ranking from query logs remains a genuinely good idea that successors copied
- Deliberately small surface area — analysts get table search, owners, column stats, and previews without a governance platform's learning curve
- Apache-2.0 under neutral LF AI & Data governance, with nothing held back for a paid tier
- Databuilder is plain-Python ETL — custom extractors are easy to write and schedule from an existing Airflow deployment
- Battle-tested at real scale by Lyft, Square, Asana, Brex, and others during its 2019–2023 heyday
- Development has effectively stalled — last release August 2024 (databuilder 7.5.1), last monorepo commit April 2025 (moving a maintainer to emeritus)
- No managed offering exists — Stemma, the commercial managed Amundsen, was acquired by Teradata in 2023 and discontinued
- Discovery only — no business glossary, governance workflows, data contracts, or PII auto-classification
- Lineage is a table-level bolt-on (OpenLineage file extractor plus a lineage tab), far behind DataHub and OpenMetadata column-level lineage
- Heavy operational stack for frozen software — Neo4j, Elasticsearch, and three services to run and patch yourself
- Community momentum moved to DataHub and OpenMetadata; both publish well-trodden Amundsen migration guides
What Amundsen actually is.
What Amundsen actually is
Amundsen is the data catalog Lyft built internally and open-sourced in October 2019, and the project that made search-first discovery the default shape of the category. The core insight — rank search results by usage from query logs, so the tables people actually query float above abandoned ones — was genuinely novel in 2019, and every catalog since has copied it. Architecturally it is a set of microservices: a Flask/React frontend, a search service backed by Elasticsearch, a metadata service backed by Neo4j, and Databuilder, a plain-Python ETL framework that pulls metadata from warehouses, dashboards, and dbt on a schedule (typically as Airflow DAGs). It joined LF AI & Data as an incubation project in August 2020.
The maintenance question
This is a know-what-you’re-getting-into entry. The honest state in mid-2026: the repository sits at roughly 4,800 stars and 216 historical contributors, but the last release was databuilder 7.5.1 in August 2024, commits through late 2024 were mostly dependency bumps plus one search-logging patch from Square, and the final commit to the monorepo — April 2025 — moved a maintainer to emeritus status. The repo is not archived and nothing stops you from running it, but no one should plan around new features, and security patches are best assumed to be your own responsibility.
The commercial story ended earlier. Stemma, founded by an Amundsen co-creator to sell a managed cloud version, was acquired by Teradata in 2023 and discontinued as a standalone product. Since then there has been no managed Amundsen, and both OpenMetadata and DataHub publish step-by-step migration guides aimed squarely at Amundsen installations.
Where it fits against the alternatives
Against datahub and openmetadata, the comparison is mostly historical: both cover Amundsen’s discovery core, then add business glossary, governance workflows, column-level lineage, and data quality — with active communities shipping monthly. Amundsen’s remaining edge is smallness: if your entire requirement is usage-ranked table search with owners and column stats, Amundsen does that with less conceptual overhead than either successor. Against apache-atlas, Amundsen is the friendlier UX but the less-maintained codebase; Atlas persists inside Hadoop-legacy estates Amundsen never targeted. Against select-star or secoda, the trade is self-hosted OSS versus paying for a maintained SaaS that does the same search-first job.
How to evaluate it
If you are evaluating catalogs fresh, evaluate DataHub and OpenMetadata first — either is the stronger default, and both are free to self-host. Amundsen is worth serious evaluation in exactly two situations: you have an existing deployment and are deciding when (not whether) to migrate, or you want the smallest possible discovery layer and are staffed to own a frozen Apache-2.0 codebase outright. In the first case, run the OpenMetadata or DataHub migration guide against a staging copy and time the effort. In the second, be honest about the operational bill: Neo4j, Elasticsearch, and three services patched by you, indefinitely, for software that will not improve.
All capabilities by cluster.
Catalog & discovery
Primary · strength 3/3Lineage & metadata
Secondary · strength 1/3Where it plugs in.
Native warehouse support
Orchestrators & pipeline tools
The honest pricing breakdown.
Free tier Fully open source under Apache-2.0; no paid tier exists. Run cost is your own infrastructure (frontend, search, and metadata services plus Neo4j and Elasticsearch).
Full Amundsen pricing breakdown — model, cost factors, alternatives by price →
What it doesn't do.
A managed vocabulary of business terms ("Active Customer", "Recognized Revenue") with definitions, owners, and — critically — links to the physical assets that implement them. Without the linking layer a glossary is just a wiki. With it, you can answer "which dashboards use our official definition of Active Customer?" — the question governance teams actually care about.
Column-Level Lineage →Traces data flow at the individual column granularity rather than just between tables. Critical for impact analysis when a column changes, for PII tracking, and for regulatory compliance in financial or healthcare contexts. Column-level lineage is computationally expensive and not all tools that claim "lineage" actually provide it — many stop at table level.
PII Auto-Classification →Automatically identifies columns likely to contain personally identifiable information — email addresses, phone numbers, national IDs — through regex, name heuristics, or ML. Required for meaningful compliance workflows at scale. Quality varies: naive implementations produce heavy false-positive rates. Worth asking vendors about their accuracy benchmarks.
Data Contracts →Explicit, versioned agreements between data producers and consumers specifying schema, semantics, SLAs, and breaking-change policy. Enforced in CI for producers and at consumption time for consumers. Distinct from schema validation alone — a contract captures intent, not just structure. Implementations vary wildly; many tools claiming "data contracts" offer only schema checks.
Drill into one capability.
Other key features
If not Amundsen, then what?
Common alternatives
Teams typically migrate to
See all 9 Amundsen alternatives, scored and compared →Quick answers.
- Is Amundsen open source?
- Yes. Amundsen is open source under the Apache-2.0 license, and can be self-hosted at no license cost. A paid managed tier is also offered.
- How much does Amundsen cost?
- Amundsen publishes pricing, starting around $0 custom. A free tier is available: Fully open source under Apache-2.0; no paid tier exists. Run cost is your own infrastructure (frontend, search, and metadata services plus Neo4j and Elasticsearch).
- How is Amundsen deployed?
- Amundsen is self-hosted — you run it in your own infrastructure.
- Does Amundsen work with dbt and my warehouse?
- It integrates with dbt via plugin. Amundsen supports snowflake, bigquery, redshift, databricks, postgres, plus 4 more.
More catalog & discovery tools
Provenance.
Last verified 2026·07·03 against vendor documentation and, where possible, hands-on trial. Spot something off? Send a correction →