DuckDB 2.0 Turns the In-Process Database into a Server
A Preview of DuckDB v2.0
DuckDB v2.0, code-named Cyanoptera, introduces a client/server mode via the Quack extension and the new CONNECT statement, allowing any DuckDB process to serve databases over the network. The release also brings triggers, a first-class VARIANT type, asynchronous I/O, a new SQL parser, and a new storage format. Performance gains are dramatic: a recursive query benchmark runs 40× faster than v1.5.4.
Where last year was the year of the lakehouse, this release kicks off the year of DuckDB as a server.
- otter-in-a-suit
Super excited about Quack (partially due to the name). I use duckdb for both analytics and runtime, but I do have to serve/handle/manage a giant, multi-GiB duckdb file as effectively a runtime artifact[1]. I'm aware that this isn't the _perfect_ database for this, but the mix of it being fast, having spatial support, sane coding interfaces, great dbt integration, and me being able to do everything between "run a giant several hundred step dbt pipeline" to "query the output of said pipeline" to "read/query a csv on disk" with the exact same tool is just so nice. If I could centrally manage said asset more akin to a traditional database, I'd be very happy.
I've partially solved this with separate databases for different steps in the data pipeline(s) and have even experimented with Clickhouse as a complete alternative, but I really like way too many things about duckdb to replace it.
[1]: If you care: https://skaldmaps.com/blog/2026/07/zip-codes-are-a-bad-spati...
- jtbaker
DuckDB is one of the things I've been most excited about in a long time. Introduced it to projects at 3 companies since 2023, greatly lowering resource requirements and running it in a variety of environments. Just having the ability to do out of core bigger than memory data processing on lower end consumer grade hardware is remarkable.
Thanks to the team for everything!
- therealdrag0
Hate to bring it up, but 10,000 commits in less than 6 months is a lot. Is AI a major contribute here?
Is AI use for accelerated development of a beloved tool like DuckDB enough to quiet lingering doubters?
- dm03514
<3 duckdb run realtime analytics pipeline using a (moderately popular) stream processing engine I built on top of DuckDB. Looking forward to what duckdb provides in terms of perf out of the box!
https://github.com/turbolytics/sql-flow
DuckDB has been a fantastic engine to build on (in python), and processes thousands of events per second, day in an day out, without issue
- gw32
> The VARIANT type shipped in DuckDB v1.5, and the way to think about it is JSON on steroids. Basically, imagine if JSON were fast. [...] DuckDB automatically detects the common structure hidden in your semi-structured data and “shreds” it, so it compresses well in storage
I am really looking forward to this hitting v2.0. I can't stand uncompressed JSON - so space-inefficient. But heterogenous JSON in parquet files is such a pain because of schema differences causing fields to be silently dropped. Having DuckDB solve this is exactly what I've been looking for.
- srameshc
I <3 DuckDB. It has become one of my go to tools for storing, data processing , integrations and now even graph. More importantly it's fun to use because it is so portable. Looking forward to v2.
- remywang
If you like DuckDB, please consider funding DB research [1]!
- aleda145
Excited about a stable C++ API for extensions!
I made a dry run extension a few months ago (https://github.com/aleda145/duckdb-dryrun), will be so nice to build it just once and know that it will always work.
Also urge anyone to make an extension, the template makes it quite smooth: https://github.com/duckdb/extension-template