Snowflake-Labs/pg_lake

Health v2 · maintenance only

Adoption not part of the score

1625 stars · 114 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

pg_lake is a set of PostgreSQL extensions that turn Postgres into a lakehouse engine for Apache Iceberg tables and raw data lake files in object stores like S3. It combines Postgres transactions with DuckDB's query engine to query, import, and export Parquet, CSV, JSON, Iceberg, and geospatial formats using plain SQL.

Use cases

• query parquet files in s3 from postgres
• create and manage iceberg tables with sql
• build a postgres lakehouse with transactional guarantees
• import csv and files from object storage into postgres tables
• export query results to parquet in s3
• read geo and shapefiles with sql
• run dbt models on iceberg tables
• combine local tables and external data lake files in one query

When to choose

• you want iceberg table management and data lake queries without leaving postgres
• you need transactional lakehouse semantics on icebberg tables
• you want duckdb performance behind a postgres interface
• your data lives in s3-compatible object storage in parquet, csv, or

When to avoid

• you need a managed cloud lakehouse service rather than self-hosted extensions
• your workload is purely OLTP with no data lake files
• you cannot run additional sidecar processes like pgduck_server
• you require engines other than postgres and duckdb to write your iceberg tables

Facets

library · maturity active

database database-driver etl geospatial search-engine databases big-data analytics developer-tools self-hosted python iceberg lakehouse postgres-extension duckdb parquet s3 object-storage sql data-engineering linux macos docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Snowflake-Labs/pg_lake")