221–230 of 311 posts
Goodbye DuckDB and hello surprise enterprise DuckDB that has special features that you can't live without that only work with Enterprise DuckDB.
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Man I admire AWS marketing team for convincing people DynamoDB is a very good product. 100 items max per Transaction BatchGet 100 items, 16 MB max low write limits on same key Item size 400 KB max etc.
The reason it's good is because, although it is bad, you never have to worry about it in terms of maintenance, admin or scale. It's like lambda for databases. For the same price, you can run a much more capable PSQL instance with way better features, but now you're on the hook for it being up 24/7.
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indexes are very weak in duckdb, need to fit memory.
This fall, DuckDB will support larger than memory indexes! I'm really excited about it. https://duckdb.org/2026/08/17/duckdb-20-highlights#7-storage...
People using DuckDB, what's your use case? I use sqlite for a lot of my personal projects. What's a good use case for using DuckDB?
I'm an idiot, and a lot of Hacker News goes over my head, but I still read it. Would anyone mind answering this question? Are databases not a solved problem? Why are there lots of different databases? Why is one faster than the other? What's different between them?
Every tool is a trade off between effort to create vs power of the solution.
Effort is generally expensive so most things settle on some general purpose local maximum. If you had infinite effort available, you could build bespoke hardware and software from the ground up to solve every problem. It would be faster and more power efficient than any solution available today.
CPUs win out over integrated circuits because the same CPU can be used for ~every software problem, so by using a CPU you benefit from everyone pooling their efforts to improve the general purpose CPU rather than their own specific niche. But when you reach a certain scale/requirements it makes sense to do something more specific. This is one reason why we have standardized GPUs. Still general purpose but more specialized than a CPU. Or think about how Bitcoin mining moved to ASICs, because they need to do one specific thing as fast and as power efficiently as possible.
So for databases, when you get to specific scale and requirements the same kind of specialization starts to make sense. DuckDB or Clickhouse for analytical loads, TigerBeetle for high scale transactional stuff, etc. And that scale is aggregated across ~all software users, i.e. scale of analytical workloads being big enough to support analytical DBs.
Also as time goes on and industries develop the cost to develop specific solutions can go down.
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RMS addressed the business model from the very beginning: it's services and consulting. He practiced what he preached. You might think that's got a very low ceiling. But, even though it's a bad example in many ways, OpenAI showed that the ceiling is very high. And if you're morally flexible even higher.
RMS promotes GPL, not MIT licensed software. When a bigger entity (e.g. AWS) decides to undercut the original creator/vendor (e.g. redis,elastic search), MIT code des not help.
The title is misleading. AWS acquired DuckLabs, NOT DuckDB. The DuckDB source code is still owned by the nonprofit DuckDB Foundation. Quote from the article: "As the CWI representative on the DuckDB Foundation... When DuckLabs spun out of CWI, we created this foundation, which holds all IP of open-source DuckDB, and will continue to do so." - Peter Boncz