textql VS duckdb

I like textql [0] better for this use case, as it's simpler in my mind.

[0] https://github.com/dinedal/textql

Primarily, you are right. SQL is for working with structured data and that largely covers RDBs. However, there are tools (like textql) that allow you to query CSV files and the effort works with most other text files that have some kind of structure.

As the author of textql ( https://github.com/dinedal/textql ) - thanks for the shoutout!

Looks great, I love more options in the space for CLI based data analysis tools! Fantastic work!

Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.

Reminds me of the textQL extension that's available in Asciidoc.

Point it to an external CSV file, enable TextQL, and bam, there's your query returned as a table. Handy for parts lists, inventory, that kind of crap.

https://github.com/dinedal/textql

https://gist.github.com/mojavelinux/8856117

Through more magic, you COULD of course use stuff like Spark, or easier with programs like TextQL, sq, OctoSQL.

Somewhat-kinda related, the textql extension for Asciidoctor is so dang useful it should be in core.

https://gist.github.com/mojavelinux/8856117

I use this as a "centralized parts repository" for big ol' maintenance manuals. Refresh from PDM/PLM/LSA/Whatever. Rebuild for new parts data.

Built on TextQL, natch

https://github.com/dinedal/textql

I'm not sure if the fix is reassuring or not: https://github.com/duckdb/duckdb/pull/9411/files

It's an interesting question!

The problem is that the data is spread everywhere - no choice about that. So with that in mind, how do you query that data? Today, the idea is that you HAVE to put it into a central location. With tools like Bacalhau[1] and DuckDB [2], you no longer have to - a single query can be sharded amongst all your data - EFFECTIVELY giving you a lot of what you want from a data lake.

It's not a replacement, but if you can do a few of these items WITHOUT moving the data, you will be able to see really significant cost and time savings.

[1] https://github.com/bacalhau-project/bacalhau

[2] https://github.com/duckdb/duckdb

[4] Switch to Push-Based Execution Model by Mytherin · Pull Request #2393 · duckdb/duckdb (github.com)

it depends on your query obviously.

In general, I did very deep benchmarking of pg, clickhouse and duckdb, and I sure didn't make stupid mistakes like this: https://news.ycombinator.com/item?id=36990831

My dataset has 50B rows and 2tb of data, and I think columnar dbs are very overhiped and I chose pg because:

- pg performance is acceptable, maybe 2-3x times slower than clickhouse and duckdb on some queries if pg is configured correctly and run on compressed storage

- clickhouse and duckdb start falling apart very fast because they specialized on very narrow type of queries: https://github.com/ClickHouse/ClickHouse/issues/47520 https://github.com/ClickHouse/ClickHouse/issues/47521 https://github.com/duckdb/duckdb/discussions/6696

This action installs duckdb with the version provided in input.

Duckdb: https://github.com/duckdb/duckdb - seems pretty popular, been keeping an eye on this for close to a year now.

The Parquet-Go library is very complex, not yet success to use it. So I ask whether DuckDB can provide API https://github.com/duckdb/duckdb/issues/7776