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  • Hacker News
  • I love DuckDB genuinely more than sqlite even though they do completely different things but DuckDB has like for me the perfect mix between simplicity, embedded capabilities and expressiveness. (and actual Time and Date Types).
    by mastermage
  • > 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.

    by gw32
  • If you like DuckDB, please consider funding DB research [1]!

    [1]: https://news.ycombinator.com/item?id=49336147

    by remywang
  • 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.
    by srameshc
  • What advantages does it have over SQLite in your use cases? Can you give any examples?
    by d3Xt3r
  • Ditto! Very happy with the upcoming async support! Now it'll be a nice little db for serving http traffic as well!
    by fragebogen
  • <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

    by dm03514
  • I’m mostly using Exasol these days (the concurrency and smooth scaling to multi-node is just too seductive), but with the introduction of Quack I might take another look at DuckDB. I’ll have to see how well it handles many agents reading and writing to it concurrently.
    by jinjin2
  • I am a crew member of Joy Of Coding (https://joyofcoding.org) where we invited Hannes to do a talk. He is a great speaker. Seeing this we will need to invite him another time!
    by ivolimmen
  • 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?

    by therealdrag0
  • If you merge PRs that have commit mesages like this, it's easy to arrive at 10000 commits in 6 months:

        rename to NodePointer instead
    format
    Revert "format"
    Revert "rename to NodePointer instead"
    rename to OptionalNodePtr
    woops
    update comment
    slot renames
    more renames
    Source: https://github.com/duckdb/duckdb/pull/23605

    If every Ctrl+S is a commit, it'll go up fast.

    "woops"!

    by nh2
  • Love DuckDB. It’s so fast and portable! I mainly use the query engine as part of my ETL process for creating SQLite database. I’d love to pitch it at work, but we’re heavily invested in BigQuery, which makes it a bit difficult.
    by MILP
  • 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!

    by jtbaker
  • My favourite is AWS Athena (backed by Trino).

    "If we use this we get indefinite RAM indefinite CPU and do not need to host a server".

    I had an impression that DuckDB was not great at distributing work to other machines, but good at doing it locally? Am I wrong?

    by fifilura
  • Curious to learn more about how people are using it?

    Are they downloading parquet files and running analyses locally, or are they connecting to Iceberg-like data lake and leveraging DuckDBs query engine capabilities or have you exposed an interface (REST, UI) to query your data?

    by throwaw12
  • 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...

    by otter-in-a-suit
  • Check it out Arc, I think that we can help there, plus, use DuckDB as a engine: https://github.com/Basekick-Labs/arc
    by ignaciovdk
  • Nice post and you have me checking out your broader site and product!
    by grvdrm
  • > to "read/query a csv on disk"

    I discovered DuckDB looking for a way to analyze Nginx access.log's and it's an amazing tool. I believe it should be a standard tool like ripgrep for devs.

    by dmix
  • I built a platform for some midsize companies in a specific vertical that is basically a data warehouse with some LLM-driven dashboarding and query tools on top. Typical data size 5-150gb. So I built a service layer around duckdb, where each tenant gets their own duckdb. I'm also in the boat of knowing that duckdb is not the perfect solution for this (the classic use case is running it against local data on a laptop), but there's so much I like about it, and it's really nice that each tenant can have total separation with custom schemas and that it's straightforward to pile data into object storage and form your own lake.

    And now with things like quack the sharp points around concurrency are relaxing, and it feels like the compromises of using it this way are disappearing.

    by mediaman
  • We have bet early on DuckDB and Ducklake for Windmill and couldn't be happier. The focus on server/client mode is interesting, it opens the way for orchestrators like ours to have "lite" workers/jobs for duckdb that connect to one central bigger beefy nodes and improve the overall efficieny. I'm very curious if benchmark shows that there are performance benefits to do so thanks to co-location and overall less cpu cycles wastes.
    by rubenfiszel