DuckDB v2.0, code-named Cyanoptera, is planned for release this fall with a client/server mode, a new storage format and SQL parser, triggers, expanded semi-structured data support, and asynchronous I/O. More than 10,000 commits have been made since DuckDB v1.5 was released in March. The Quack extension will become stable, allowing a DuckDB process to serve databases over the network; the CONNECT statement can route queries to DuckDB, PostgreSQL, or MySQL servers. DuckDB says its transactional MVCC architecture supports multi-connection workloads. The release expands the VARIANT type for schema-flexible data, including storage-level execution, Parquet read/write support, and variant functions. SQL additions include BEFORE and AFTER triggers, approximate nearest-neighbor joins, data-modifying CTEs, nested schemas, JSON mutation functions, and recursive CTE aggregation. Async I/O will support Parquet, CSV, DuckDB files, and Parquet writes, targeting faster network-storage queries. A preview benchmark reports a recursive graph query falling from 4.90 seconds in v1.5.4 to 0.12 seconds in v2.0. The new storage format pages indexes into memory on demand, while a PEG-based parser enables grammar extensions and a Spark compatibility mode. DuckDB also replaces ICU with an extension using compressed IANA timezone data and broadens its stable C API so extensions can remain compatible across versions.

DuckDB provides in-memory column-major data processing tools optimized for laptops, now available in Clojure. The tech.ml.dataset (TMD) platform allows users to handle large datasets by operating on samples or filtering subsets, and supports data persistence with nippy, arrow, or par.