(Last updated: October 2025)

The DuckDB project is governed by the non-profit DuckDB Foundation. The Foundation and DuckDB Labs are not funded by external investors (e.g., venture capital). Instead, the Foundation is funded by contributions from its members, while DuckDB Labs' revenue is based on commercial support and feature prioritization services.

This list was compiled by the DuckDB maintainers and is based on the long-term strategic vision for the DuckDB project and general interactions with users in the open-source community (GitHub Issues and Discussions, social media, etc.). For details on how to request features in DuckDB, please refer to the FAQ item “I would like feature X to be implemented in DuckDB”.

Planned Features

This section lists the features that the DuckDB team plans to work on in the coming year.

• Migration and documentation to C client API and C extension API
• Rust support for extensions
• Improvements to lakehouse formats
  • Improved support for the Iceberg format through the iceberg extension. This was partially implemented in v1.4.0, which can write to Iceberg tables.
  • Improved support for Delta Lake through the delta extension.
  • In May 2025, we released DuckLake, a new lakehouse format. We would like to emphasize that we are still committed to developing both the iceberg and delta extensions. We also strive to provide interoperability between DuckLake and other lakehouse formats.
• MATCH RECOGNIZE for pattern matching
• GEOMETRY type
• Distribution of Windows ARM64 extensions
• Support for async I/O
• Parallel Python UDFs

Please note that there are no guarantees that a particular feature will be released within the next year. Everything on this page is subject to change without notice.

Future Work / Looking for Funding

There are several items that we plan to implement at some point in the future. If you would like to expedite the development of these features, please get in touch with DuckDB Labs.

• Go support for extensions
• Distribution of musl libc binaries
• Time series optimizations
• Partition-aware optimizations
• Sorting-aware optimizations
• Better filter cardinality estimation using automatically maintained table samples
• ALTER TABLE support for adding foreign keys
• Improvements of query profiling (especially for concurrently running queries)
• Materialized views
• Support for PL/SQL stored procedures
• Generic ODBC catalog, similarly to the existing PostgreSQL / MySQL / SQLite integrations
• XML read support