Select Star.
Founded 2020 · San Francisco, California, United States
Status · ● acquired
Verified · ● 6d ago
Automated data catalog with column-level lineage parsed from query logs — being acquired by Snowflake to power Horizon Catalog.
Where it fits — and where it doesn't.
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.
You need open-source or self-host portability (proprietary SaaS only), a data-quality engine (no monitoring, testing, or anomaly detection — pair with a dedicated tool), or a firm standalone roadmap: Snowflake's acquisition was announced November 2025, the public pricing page is already gone, and buyers on non-Snowflake stacks should assume the centre of gravity moves toward Horizon Catalog.
Enterprises wanting the broadest connector coverage or heavyweight stewardship workflows are better served by Atlan, Alation, or Collibra.
The honest scorecard.
- 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
- Broad BI lineage coverage — twelve BI integrations including Tableau, Power BI, Looker, Mode, Sigma, ThoughtSpot, QuickSight, and Hex
- OpenLineage consumer support brings pipeline lineage (e.g. Airflow) into the same graph as warehouse and BI lineage
- Pending Snowflake acquisition (announced Nov 2025) makes the standalone roadmap uncertain — the stated plan folds the technology into Horizon Catalog, a real risk for non-Snowflake stacks
- No published pricing — the /pricing page has been removed outright and now redirects to the homepage; evaluation requires a sales motion
- Proprietary SaaS only — no open-source path and no self-hosted deployment
- No data-quality capability — no monitors, tests, anomaly detection, or contracts; it observes metadata, not data values
- Smaller connector catalog (~28 documented integrations) than Atlan, Alation, or Collibra, with several warehouse connectors (MSSQL, MySQL, Oracle) still in beta
- No public SDK or Terraform provider; the REST API covers metadata and lineage but is thinner than API-first catalogs
What Select Star actually is.
What Select Star is
Select Star is an automated data catalog and lineage platform — the company’s own framing is “metadata context platform” — founded in San Francisco in 2020 by Shinji Kim. Its core mechanic: connect read-only to your warehouse and BI tools, parse the SQL query logs and dbt manifests, and generate column-level lineage, popularity metrics, entity-relationship diagrams, and suggested documentation automatically. Around that core sit Ask AI (natural-language search over the catalog), an MCP server that exposes metadata and lineage to LLM agents, automated semantic model generation, and a Data Access Control module with automated PII tagging, tag propagation, and RBAC/ABAC policies. On November 24, 2025, Snowflake announced a definitive agreement to acquire the team and platform technology, with the stated goal of expanding Horizon Catalog for agentic AI experiences like Snowflake Intelligence and Cortex Code.
Where it fits
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.
On the Snowflake acquisition
The announcement is unambiguous about direction: Select Star’s lineage and discovery capabilities are headed into Snowflake’s Horizon Catalog. That cuts both ways. For Snowflake-centric organisations it is arguably good news — best-in-class automated lineage becoming a native platform capability. For everyone else it introduces real uncertainty: the public pricing page has already been removed, and the long-term standalone product, its cross-platform integrations, and its commercial terms are all open questions until the transition settles. Kim’s announcement says the multi-source integrations will be brought into Horizon Catalog, but a Snowflake-owned catalog’s incentives on BigQuery or Databricks coverage are not the same as an independent vendor’s.
How to evaluate it
Scope any trial around the automation claim, because that is the whole pitch: connect one warehouse, one dbt project, and one BI tool, then check whether column-level lineage materialises accurately across all three without manual stitching, and whether the auto-generated documentation and popularity signals actually help analysts find the right table. Then ask the acquisition questions directly — standalone availability for new customers, support commitments for non-Snowflake sources, and what happens to your contract when the technology folds into Horizon Catalog. If you are already all-in on Snowflake, the safest read may be to evaluate Horizon Catalog’s roadmap rather than Select Star as a standalone purchase.
All capabilities by cluster.
Catalog & discovery
Primary · strength 3/3Lineage & metadata
Secondary · strength 2/3Where it plugs in.
Native warehouse support
Orchestrators & pipeline tools
The honest pricing breakdown.
Sales-only tier All pricing is sales-led with no listed numbers; the former /pricing page now redirects to the homepage. Post-acquisition availability and terms for new standalone customers should be confirmed directly.
Full Select Star pricing breakdown — model, cost factors, alternatives by price →
What it doesn't do.
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.
ML Anomaly Detection →Uses machine learning models trained on historical data to detect values, volumes, or distributions outside expected bounds — without requiring the user to write explicit assertions. Reduces the "I didn't know to test for that" class of incident. Trade-off: requires a training window (typically two to four weeks), can produce false positives on seasonal data, and doesn't replace assertions for business-rule validation.
Circuit Breaker →Halts downstream execution when a test fails — preventing bad data from propagating into marts, ML features, or BI dashboards. Requires tight integration with the orchestrator (Airflow, Dagster, dbt Cloud). Distinct from alerting-only tools which notify after damage is done.
Warehouse-Native Monitoring →Monitors tables directly in the warehouse via query log parsing or scheduled metric queries — independent of the pipeline that produced the data. Catches issues regardless of which tool wrote the data, including ingestion-layer problems dbt can't see. Trade-off against dbt-native testing: reactive rather than preventive, and adds warehouse cost.
Drill into one capability.
Other key features
If not Select Star, then what?
Common alternatives
Quick answers.
- Is Select Star open source?
- No. Select Star is a proprietary product.
- How much does Select Star cost?
- Select Star does not publish list pricing — it is sales-led, so you request a quote. There is no free tier.
- How is Select Star deployed?
- Select Star is a managed cloud (SaaS) product.
- Does Select Star work with dbt and my warehouse?
- It has a native dbt integration. Select Star supports snowflake, bigquery, redshift, databricks, postgres, plus 2 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 →