JDBC

Colrows ships a JDBC driver that exposes the semantic execution layer as a familiar SQL endpoint. Point Tableau, Power BI, DBeaver, JetBrains, dbt, or any other JDBC client at it - they all inherit governed compilation without changing their workflow.

Driver download

Download the latest signed driver from Settings → Drivers → JDBC. The artifact is a single fat JAR (colrows-jdbc-1.5.x.jar, ~7 MB) with no external dependencies.

Connection string

jdbc:colrows://api.colrows.com/v1?workspace=acme&persona=regional_analyst

Authentication is via API key passed as the JDBC password (the username is ignored). Example for DBeaver:

URL:      jdbc:colrows://api.colrows.com/v1?workspace=acme
Driver:   com.colrows.jdbc.Driver
User:     (any)
Password: cl_live_8a2c…

What's different from a "raw" warehouse driver

Compilation in the loop. Every SELECT the client issues is parsed, bound, planned, and dialect-translated through Colrows. The warehouse only ever sees a governed, dialect-perfect statement.
Catalog reflection returns the semantic graph, not raw schemas. Your BI tool sees governed concepts and dimensions instead of a thousand internal tables.
Persona-aware metadata. Two analysts pointing the same Tableau workbook at Colrows see different catalogs because their personas resolve different allowed subgraphs.
Trace IDs in result sets. Every result includes a __trace_id column that resolves to the full audit trace.

Tested clients

Tool	Notes
Tableau Desktop / Server	Use as "Other databases (JDBC)". Custom dialect file included in the driver bundle.
Power BI Desktop	Via the JDBC custom connector framework. Power Query M template provided.
Microsoft Excel	Through the Power Query JDBC bridge.
DBeaver / DataGrip	First-class. Add the driver JAR; metadata browsing works out of the box.
dbt	Use the `dbt-colrows` adapter. Models compile through the semantic layer.
Apache Superset	Use the JDBC SQLAlchemy dialect.

Why this matters.

Most semantic-layer tools force you to throw away your BI investment. The Colrows JDBC driver lets your existing tools enjoy compile-time governance with zero migration.

Limitations

The driver supports SELECT and metadata reflection only. INSERT / UPDATE / DDL are not exposed - Colrows is a semantic execution layer, not a write path.
Some BI tools cache catalog metadata aggressively; refresh the connection after promoting new concepts.
Streaming result sets are paginated server-side; very large extracts should use the HTTP API's async export endpoint instead.