whichdb
vs

DuckDB vs pg_lake

DuckDB: In-process columnar SQL database: the SQLite of analytics, running inside your app or notebook. pg_lake: Postgres extensions from Snowflake that read and write Iceberg tables and lake files, executed via DuckDB.

key differences

  • DuckDB is primarily a columnar / OLAP database; pg_lake is relational.
  • Only DuckDB has secondary indexes, full-text search, vector search, in-memory, encryption at rest.
  • DuckDB can run embedded in your application process.

choose duckdb for

  • +Local data analysis in notebooks
  • +ETL and data-engineering pipelines on files
  • +Embedded analytics inside applications
  • +Querying data lakes on S3 without a cluster

best at · OLAP, Embedded, Lakehouse

choose pg-lake for

  • +Giving Postgres apps access to an Iceberg lake
  • +Exporting Postgres data to Parquet/Iceberg
  • +Small lakehouse on Postgres
  • +Querying raw files in S3 from SQL

best at · Lakehouse, OLAP, Warehouse

DuckDBIn-process columnar SQL database: the SQLite of analytics, running inside your app or notebook.
pg_lakePostgres extensions from Snowflake that read and write Iceberg tables and lake files, executed via DuckDB.
overview
Primary model
Columnar / OLAP
Relational
Also supports
Relational, Document, Spatial, Vector
Columnar / OLAP, Spatial
Type
Database engine
Extension
Status
Active
Active
Developer
DuckDB Foundation / DuckDB Labs
Snowflake (Snowflake Labs)
First release
2019
2025
Latest version
2.0.0 (Oct 21, 2026)
3.5.9 (Oct 25, 2026)
License
Open source (permissive)MIT License
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
63.7
15.2
Rank
#13
#220
GitHub stars
42.6K
1.7K
Stack Overflow questions
501
–
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Medium (≤ 10 TB)
Horizontal scaling
None
None
Multi-region
None
None
ACID
Full
Full
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Embedded, Single node, In memory
Single node, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
—
Serverless
—
—
Embedded
✓
—
Edge
—
—
Clouds
–
–
capabilities
Transactions
✓
✓
Joins
✓
✓
Secondary indexes
✓
—
Full-text search
✓
—
Vector search
✓
—
Geospatial
✓
✓
JSON
✓
✓
Change data capture
—
—
Triggers
—
—
Stored procedures
—
—
Materialized views
—
—
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
✓
✓
In-memory
✓
—
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
✓
—
Role-based access
—
—
Time travel
—
—
Branching
—
—
Online schema changes
—
—
Streaming ingest
—
—
Offline sync
—
—
Runs in WebAssembly
✓
—
interfaces
Query languages
SQL (PostgreSQL-like dialect)
SQL, PL/pgSQL
Client languages
Python, R, Java, JavaScript, Go, Rust, C, Swift
C, Java, Python, JavaScript, Go
Best for
OLAP, Embedded, Lakehouse, Warehouse
Lakehouse, OLAP, Warehouse
Add more to this comparisonNot sure either fits? Try smart match

DuckDB vs pg_lake: FAQ

What is the difference between DuckDB and pg_lake?

DuckDB: In-process columnar SQL database: the SQLite of analytics, running inside your app or notebook. pg_lake: Postgres extensions from Snowflake that read and write Iceberg tables and lake files, executed via DuckDB. DuckDB is primarily a columnar / OLAP database; pg_lake is relational. Only DuckDB has secondary indexes, full-text search, vector search, in-memory, encryption at rest. DuckDB can run embedded in your application process.

When should I choose DuckDB over pg_lake?

Choose DuckDB for local data analysis in notebooks; ETL and data-engineering pipelines on files; and embedded analytics inside applications. Choose pg_lake for giving Postgres apps access to an Iceberg lake, exporting Postgres data to Parquet/Iceberg and small lakehouse on Postgres.

Is DuckDB or pg_lake more popular?

DuckDB ranks #13 on the WhichDB Score (63.7/100) and pg_lake ranks #220 (15.2/100). Popularity is not fit: check the requirements that matter for your project.

Are DuckDB and pg_lake open source?

Yes. DuckDB is open source. License: MIT License. Yes. pg_lake is open source. License: Apache License 2.0.