Amundsen vs Select Star.
Amundsen and Select Star both anchor in catalog & discovery — 7 dimensions differ, 1 hold. Below: posture, coverage diff, and capability matrix.
The Lyft-born OSS catalog that invented search-first discovery — historically important, but development has largely stalled since 2024.
Automated data catalog with column-level lineage parsed from query logs — being acquired by Snowflake to power Horizon Catalog.
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.
Data teams on Snowflake, BigQuery, Databricks, or Redshift plus dbt and a mainstream BI tool who want a catalog that documents itself — column-level lineage, popularity metrics, ER diagrams, and auto-generated docs parsed from query logs rather than curated by hand.
What each is betting on.
Honest read: maintenance mode. Created at Lyft, open-sourced October 2019, joined LF AI & Data as an incubation project in August 2020. Development has slowed to near-zero — the last release was databuilder 7.5.1 (August 2024) and the last commit to the monorepo (April 2025) moved a maintainer to emeritus status. Stemma, the managed-Amundsen company founded by an Amundsen co-creator, was acquired by Teradata in 2023 and discontinued as a standalone product. The repo is not archived, but treat this as software that is no longer evolving.
Snowflake announced a definitive agreement to acquire Select Star's team and platform technology on November 24, 2025 (Snowflake blog; Select Star blog by founder/CEO Shinji Kim). Terms undisclosed. Stated plan: fold Select Star's lineage and discovery into Snowflake's Horizon Catalog to power agentic experiences like Snowflake Intelligence and Cortex Code. Founded 2020 in San Francisco. The public /pricing page has been removed (it now redirects to the homepage).
Each tool's current strategic narrative, verbatim from its profile.
How each tool describes the other.
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.
Select Star cross-shops with atlan, secoda, alation, and collibra among proprietary catalogs, and with datahub, openmetadata, and amundsen on the open-source side — its own site maintains comparison pages against most of these. Its wedge has always been automation-first lineage: where enterprise suites lead with stewardship workflows and OSS catalogs lead with portability, Select Star leads with column-level lineage extracted from query logs with minimal setup, proven at unusual scale (Block used it to automate lineage across an exabyte-scale warehouse). It consumes OpenLineage events, so Airflow and pipeline lineage land in the same graph as warehouse and BI lineage. What it is not is a data-quality engine: there are no monitors, tests, or anomaly detection, which is why the quality-testing cluster scores zero — pair it with a dedicated tool if you need runtime checks.
Each quote is pulled from the named tool's own "Where it fits" write-up.
Spec sheet diff.
| Amundsen | Select Star | |
|---|---|---|
| Vendor | LF AI & Data Foundation | Select Star (Snowflake) |
| Deployment | Self-hosted only | SaaS only |
| License | Open source | Proprietary |
| Pricing | OSS · paid tiers | Contact sales |
| Free tier | Yes | No |
| OSS self-host | Yes | No |
| dbt integration | Plugin | Native |
| Founded | 2019 | 2020 |
| HQ | — | San Francisco, California, United States |
| Status | ● active | ○ acquired |
Full Amundsen pricing → Full Select Star pricing →
Both share Primary cluster: Catalog & discovery · OpenLineage: Consumer
Each tool's center of gravity.
| Cluster | Amundsen | Select Star |
|---|---|---|
| Lineage & metadata | 1/3 | 2/3 |
| Quality & testing | 0/3 | 0/3 |
| Catalog & discovery | 3/3primary | 3/3primary |
Scored 0–3 per cluster on the same rubric across all tools. A 0 means the cluster isn't the tool's focus, not that the feature is absent. See the methodology.
Where they cover different ground.
The declared feature set.
5 of 6 declared features differ — listed first.
These are each tool's self-declared key_features; a blank dot means
undeclared, not impossible.
| Feature | Amundsen | Select Star |
|---|---|---|
| Business Glossary Catalog & discovery | ||
| PII Auto-Classification Catalog & discovery | ||
| Column-Level Lineage Lineage & metadata | ||
| Reverse Impact Analysis Lineage & metadata | ||
| Transformation Lineage Lineage & metadata | ||
| Table-Level Lineage Lineage & metadata |
Where they disagree.
Catalog & discovery
6 of 9 differ| Amundsen | Select Star | |
|---|---|---|
| Business glossary | ||
| NL search | ||
| Governance flows | ||
| PII auto-classify | ||
| Tag propagation | ||
| Free self-host |
Lineage & metadata
3 of 7 differ| Amundsen | Select Star | |
|---|---|---|
| Column-level | ||
| Cross-system | ||
| Reverse impact |
When to pick each.
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.
Data teams on Snowflake, BigQuery, Databricks, or Redshift plus dbt and a mainstream BI tool who want a catalog that documents itself — column-level lineage, popularity metrics, ER diagrams, and auto-generated docs parsed from query logs rather than curated by hand. A natural fit for lean-governance organisations that want automated PII tagging with propagation instead of a steward-heavy programme, and for Snowflake-centric shops that read the pending acquisition as a roadmap tailwind: the technology is slated to become part of Horizon Catalog.
What each does best.
Amundsen stands out for
- 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
Select Star stands out for
- Automated column-level lineage parsed from warehouse query logs is the differentiator — proven at very large scale (Block's case study covers lineage automation at exabyte scale)
- Fast time-to-value — auto-generated documentation, popularity/usage metrics, and entity-relationship diagrams appear from metadata without manual curation
- Governance automation — automated PII tagging with tag propagation through lineage, plus RBAC/ABAC policy controls in the Data Access Control module
- Credible AI surface — Ask AI natural-language search, an MCP server exposing metadata and lineage to agents, and automated semantic model generation
Tools both also compete with.
All Amundsen alternatives, scored →All Select Star alternatives, scored →
A note on this comparison.
Every capability value above traces to Amundsen or Select Star's own structured spec, which links back to its source — nothing here is averaged or smoothed across the two.
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