Amazon Acquires DuckLabs and Integrates DuckDB in Amazon Aurora PostgreSQL

Amazon has announced the acquisition of DuckLabs, the Amsterdam-based company behind the analytical database DuckDB.

According to the news, Hannes Mühleisen and Mark Raasveldt, creators of DuckDB and co-founders of DuckLabs, will continue to lead the team and the open-source project’s technical direction as part of AWS.

In the announcement on their blog, Mühleisen and Raasveldt explain the reasons behind the decision to join AWS:

Joining AWS gives us the resources and reach to bring this technology to many more developers and organizations, and to pursue ideas at a scale that would have been difficult for us to reach alone.

All the parties involved in the deal have reassured the community about the future of the projects maintained by DuckLabs. DuckDB and all the components of their "Duck Stack", such as DuckLake and Quack, will remain free and open-source under the MIT licence, while the non-profit DuckDB Foundation will continue its supervision of the projects.

In the announcement, Mai-Lan Tomsen Bukovec, technology vice president at AWS, explains what DuckDB was created for:

DuckDB set out to solve the problem of blazingly fast performance for the 90%+ of data queries in the world today, that often runs 1 terabyte of data or less as part of analysis and dashboarding.

She argues that DuckDB's optimisations and performance are particularly relevant in agentic AI workloads. AI agents often inspect data and run small exploratory queries before deciding how they actually want to move forward, a pattern that makes DuckDB naturally optimised for AI use cases.

The community has positively welcomed the news, though with some scepticism. On Reddit, adappergentlefolk writes:

I hope this doesn't slow the pace of innovation they have been doing, but i'm glad they found a way to both cash in on their work yet keep most of it oss under the foundation.

In a piece on Werner Vogels's blog, Andy Warfield, distinguished engineer at AWS, shares more on how the relationship between AWS and DuckLabs matured before the acquisition. He writes that the initial contact happened when the S3 team was working on S3 Tables. The collaboration then evolved, as he explains:

Over the past two years (give or take), our teams have worked more and more closely together and have broadened the areas where we’ve collaborated. We explored AWS Lambda as a matched primitive for launching DuckDB queries quickly, and we smoothed the integrations between DuckDB and the AWS database and analytics engines through DuckDB’s evolving ATTACH and CONNECT commands.

For Warfield, the deal is an opportunity to widen the co-founders' reach rather than to absorb their work:

Hannes and Mark’s vision is so aligned with the way that we think about data at Amazon that we wanted to give them the broadest possible opportunity to set the agenda not just for DuckDB, but for how analytics should be built and delivered in the cloud. So, after many conversations [...], we jointly made the decision to have the DuckLabs team join AWS.

Following the acquisition, Amazon Aurora PostgreSQL is the first service to receive a user-facing feature powered by DuckDB. Esra Kayabali, principal solutions architect at AWS, explains the type of workloads the new feature tries to simplify.

Previously, if your application needed to combine recent transactional data in Aurora with historical records stored in Amazon S3, a common approach was to build reverse ETL pipelines that duplicated data, increased infrastructure costs, and required ongoing engineering effort to keep everything synchronized.

The integration of DuckDB directly in Aurora PostgreSQL allows a single query to combine live operational data with historical data available in Apache Iceberg tables managed through AWS Glue Data Catalog, as well as Parquet and Iceberg data stored in Amazon S3 and S3 Tables. The processing of these queries stays within Amazon Aurora, without additional network hops or ETL pipelines, minimising configurations and resources.

The feature is available in all commercial regions and AWS GovCloud (US) at no additional charge, with customers paying only for the incremental Aurora compute and the S3 requests their queries generate.