OpenMetadata vs Select Star.
OpenMetadata and Select Star both anchor in catalog & discovery — 6 dimensions differ, 2 hold. Below: posture, coverage diff, and capability matrix.
Apache-2.0 unified metadata platform with a deliberately simple stack — discovery, lineage, quality, and contracts in one project.
Automated data catalog with column-level lineage parsed from query logs — being acquired by Snowflake to power Horizon Catalog.
Teams that want an OSS catalog without the operational weight of DataHub's Kafka and graph-DB architecture.
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.
Collate founded 2021 by Suresh Srinivas (ex-Hortonworks co-founder, Hadoop committer) and Sriharsha Chintalapani (Apache Kafka and Storm PMC, ex-Uber). The OpenMetadata project was launched alongside the company. Series A $10M July 2025. Differentiator vs DataHub: deliberately simpler architecture (Postgres or MySQL + Elasticsearch — no Kafka, no graph DB) and faster shipping cadence on governance features through 2024–2025 (Multi-Domain, Data Contracts GA in 1.9, Data Quality as Code).
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.
OpenMetadata's page doesn't directly mention Select Star. See the OpenMetadata detail page.
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.
| OpenMetadata | Select Star | |
|---|---|---|
| Vendor | Collate | Select Star (Snowflake) |
| Deployment | SaaS · Self-hosted | SaaS only |
| License | Open source | Proprietary |
| Pricing | OSS · free | Contact sales |
| Free tier | Yes | No |
| OSS self-host | Yes | No |
| OpenLineage | None | Consumer |
| Founded | 2021 | 2020 |
| HQ | Saratoga, CA | San Francisco, California, United States |
| Status | ● active | ○ acquired |
Full OpenMetadata pricing → Full Select Star pricing →
Both share Primary cluster: Catalog & discovery · dbt integration: Native
Each tool's center of gravity.
| Cluster | OpenMetadata | Select Star |
|---|---|---|
| Quality & testing | 2/3 | 0/3 |
| Lineage & metadata | 3/3 | 2/3 |
| 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 8 declared features differ — listed first.
These are each tool's self-declared key_features; a blank dot means
undeclared, not impossible.
| Feature | OpenMetadata | Select Star |
|---|---|---|
| Data Contracts Quality & testing | ||
| Schema Change Detection Quality & testing | ||
| Reverse Impact Analysis Lineage & metadata | ||
| Table-Level Lineage Lineage & metadata | ||
| Transformation Lineage Lineage & metadata | ||
| Business Glossary Catalog & discovery | ||
| PII Auto-Classification Catalog & discovery | ||
| Column-Level Lineage Lineage & metadata |
Where they disagree.
Catalog & discovery
3 of 9 differ| OpenMetadata | Select Star | |
|---|---|---|
| Data contracts | ||
| Access requests | ||
| Free self-host |
Lineage & metadata
1 of 7 differ| OpenMetadata | Select Star | |
|---|---|---|
| Historical |
When to pick each.
Teams that want an OSS catalog without the operational weight of DataHub's Kafka and graph-DB architecture. OpenMetadata's simpler stack — Postgres or MySQL plus Elasticsearch, no graph DB, no Kafka — makes it materially easier to stand up and keep alive. Particularly strong for shops that want one tool to cover discovery, governance, lineage, profiling, and quality together rather than glue several together. Connector breadth (120+) is the highest of the OSS catalogs, and the cadence of governance features in 2024–2025 (Multi-Domain, Data Contracts GA in 1.9, Data Quality as Code) has been faster than the competition.
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.
OpenMetadata stands out for
- Highest connector count in the OSS catalog space (120+) — particularly strong on dashboards, ML, and pipeline systems
- Deliberately simple architecture (no Kafka, no graph DB) makes self-hosting realistic for smaller platform teams
- Unified scope — discovery, lineage, governance, quality, contracts, and collaboration in one project, not a constellation of subsystems
- Faster shipping cadence on governance features through 2024–2025 (Multi-Domain, Data Contracts GA, Data Quality as Code, Auto-Tune)
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 OpenMetadata alternatives, scored →All Select Star alternatives, scored →
A note on this comparison.
Every capability value above traces to OpenMetadata 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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