Integrations
VectorFin works with
your existing data stack
Native Apache Iceberg tables. No ETL pipelines. No data copies. Connect BigQuery, Snowflake, Databricks, or pyiceberg in minutes.
Supported Platforms
BigQuery
Query VectorFin Iceberg tables directly from BigQuery with external table registration — no ETL, no copies.
Snowflake
Mount VectorFin as a native Iceberg catalog via Apache Polaris — query with standard SQL, no data movement.
Databricks
Register VectorFin Iceberg tables in Unity Catalog and query with PySpark, SQL, or MLflow — full ML pipeline support.
Apache Iceberg
Access VectorFin data directly via pyiceberg — open format, no vendor lock-in, bitemporal time-travel built in.
Python
Query VectorFin via REST API or pyiceberg — pandas DataFrames, semantic search, and full signal pipelines in Python.
dbt
Model VectorFin signals in dbt — define transforms on top of Iceberg tables, document lineage, and schedule with dbt Cloud.
Integration Comparison
| Platform | Required Tier | Setup Time | Query Language | Iceberg Native |
|---|---|---|---|---|
| Python REST API | Free | 2 min | Python | — |
| pyiceberg / Apache Iceberg | Starter | 5 min | Python | ✓ |
| BigQuery | Pro | 5 min | SQL | ✓ |
| Snowflake | Pro | 10 min | SQL | ✓ |
| Databricks | Pro | 15 min | SQL / Python | ✓ |
| dbt | Pro | 20 min | SQL | ✓ |
Ready to connect?
Start with the free tier. Upgrade to Pro for Iceberg catalog access.