llm/302a36fb-79e1-4f4b-b047-e145d20e4497/topic-2-8bdcc21e-269e-4754-86b1-9cffe2ff92ae-input.json
The following is content for you to summarize. Do not respond to the comments—summarize them. <topic> DuckDB Use Cases # Enthusiasm for DuckDB's columnar storage, JSON handling, WASM support, S3 integration, and use as analytical complement to SQLite for OLAP workloads </topic> <comments_about_topic> 1. From my perspective, everything's DuckDB. Single file per database, Multiple ingestion formats, full text search, S3 support, Parquet file support, columnar storage. fully typed. WASM version for full SQL in JavaScript. 2. DuckDB can read/write SQLite files via extension. So you can do that now with DuckDB as is. https://duckdb.org/docs/stable/core_extensions/sqlite 3. My understanding is that this is still too slow for quick inserts, because duckdb (like all columnar stores) is designed for batches. 4. very interesting. whats the vector indexing story like in duckdb these days? also are there sqlite-duckdb sync engines or is that an oxymoron 5. https://duckdb.org/docs/stable/core_extensions/vss It's not bad if you need something quick. I haven't had a large need of ANN in duckdb since it's doing more analytical/exploratory needs, but it's definitely there if you need it. 6. I would say SQLite when possible, PostgreSQL (incl. extensions) when necessary, DuckDB for local/hobbyist data analysis and BigQuery (often TB or PB range) for enterprise business intelligence. 7. It's the standard for mobile. That said, in server-side enterprise computing, I know no one who uses it. I'm sure there are applications, but in this domain you'd need a good justification for not following standard patterns. I have used DuckDB on an application server because it computes aggregations lightning fast which saved this app from needing caching, background services and all the invalidation and failure modes that come with those two. 8. FWIW (and this is IMHO of course) DuckDB makes working with random JSON much nicer than SQLite, not least because I can extract JSON fields to dense columnar representations and do it in a deterministic, repeatable way. The only thing I want out of DuckDB core at this point is support for overriding the columnar storage representation for certain structs. Right now, DuckDB decomposes structs into fields and stores each field in a column. I'd like to be able to say "no, please, pre-materialize this tuple subset and store this struct in an internal BLOB or something". 9. No mention of DuckDB? Surprising. 10. Also somewhat surprised. DuckDB traction is impressive and on par with vector databases in their early phases. I think there's a good chance it will earn an honorable mention next year if adoption holds and becomes more mainstream. But my impression is that it's still early in its adoption curve where only those "in the know" are using it as a niche tool. It also still has some quirks and foot-guns that need moderately knowledgeable systems people to operate (e.g. it will happily OOM your DB) 11. Same surprise here. However in practice, the community tends to talk about DuckDB more like a client-side tool than a traditional database 12. Why does "database" is surveys like this not include DuckDB and SQLite, which are great [1] embedded answers to Clickhouse and PostgreSQL. Both are excellent and useful databases; DuckDB's reasonable syntax, fast vectorized everything, and support for ingesting the hairiest of data as in-DB ETL make me reach for it first these days, at least for the things I want to do. Why is it that in "I'm a serious database person" circles, the popular embedded databases don't count? [1] Yes, I know it's not an exact comparison. </comments_about_topic> Write a concise, engaging paragraph (3-5 sentences) summarizing the key points and perspectives in these comments about the topic. Focus on the most interesting viewpoints. Do not use bullet points—write flowing prose.
DuckDB Use Cases # Enthusiasm for DuckDB's columnar storage, JSON handling, WASM support, S3 integration, and use as analytical complement to SQLite for OLAP workloads
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