AWS bought DuckLabs, the company behind DuckDB, in August 2026. DuckDB stays MIT-licensed and owned by the non-profit DuckDB Foundation. So far the only AWS integration is Aurora PostgreSQL querying the lake; AWS says Athena, Glue and the rest will follow "over time".
The value is developer experience. The same SQL runs on my laptop, in a test, and in a Lambda, against the same Parquet in S3. It isn't a cheaper Athena: for big scans the difference is at most about 2x, and Athena does the fan-out for you.
Use it when
- App endpoints that run many small, selective queries over the lake (per-customer dashboards, reports): sub-second when warm, no Athena polling.
- Writing and reshaping Parquet: COPY gives full control of sort order, file size and partitions, with no 100-partition limit.
- Local development and tests: the same SQL against the same S3 data from a laptop, or against sample files in CI with no AWS at all.
Don't use it when
- Scans of tens of GB to TBs per query: one Lambda reads roughly 50 GB per 15 minutes. Athena fans out for you.
- Ad-hoc analysis by people who just want a SQL console: Athena.
Pricing
Free and MIT-licensed. In Lambda you pay compute and S3 GETs: a query that reads 1 GB costs about $0.002, against $0.005 on Athena, with no 10 MB minimum per query.
Gotchas, with fixes
Gotcha: Lambda has no HOME directory, so INSTALL, LOAD and CREATE SECRET fail with "Can't find the home directory".
Fix: Run SET home_directory='/tmp' first.
Gotcha: The S3, AWS and Iceberg extensions are downloaded at runtime unless bundled: about 100 MB on every cold start.
Fix: Bundle them in the layer and SET extension_directory to it.
Gotcha: DuckDB SQL isn't Athena's (Trino) SQL. Date, array and approximate functions differ.
Fix: Test shared queries on both engines, or keep each query on one engine.
Gotcha: The layer zip is over 50 MB.
Fix: Upload the layer through S3, or use a container image.
Instead, consider
- S3 + Glue + Athena Big scans, ad-hoc questions and many concurrent users.
Worked examples
Where it fits
- A data lake: Pick 04.
App queries, writing Parquet, local dev and tests, on the same files. AWS bought the company behind it in August 2026.
- Logs without a shocking bill: Pick 03.
Search the S3 logs from a laptop or a Lambda when someone asks what happened.
Sources
- AWS and DuckLabs (AWS Big Data blog)
- DuckLabs to join AWS
- DuckDB Iceberg catalogs (S3 Tables, Glue)
- Parquet tips (sorting for pruning)
Last reviewed by Nicolas Dao