WOwooptoo·Mar 22, 2025
There's also DSQ which uses SQL instead of its own language.
https://github.com/multiprocessio/dsq
In fd: A simple, fast and user-friendly alternative to 'find'multiprocessio
dsq
Go2022–2025
multiprocessio / dsq
dsq
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
10Distinct people
25Mentions
1Explicit recommenders
3.9KGitHub stars
What to know before exploring
What it is
Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
Nice work! I have a similar tool built on SQLite [0] and there are a number of similar tools (compared in my readme) like octosql, q, textql, datasette, etc.…
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Also in these discussions
- multiprocessio/datastation · linked in 5 of the same discussions
- multiprocessio/go-sqlite3-stdlib · linked in 3 of the same discussions
- cube2222/octosql · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
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| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 19 | 0 | 19 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 5 | 0 | 5 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
25 sourcesYou might want to look at tsv-utils, or a similar project: https://github.com/eBay/tsv-utils
For the SQL part, but maybe a lot heavier, you can use one of the projects listed on this page: https://github.com/multiprocessio/dsq (No longer maintained, but has links to lots of other projects)
In Tracking SQLite Database Changes in GitMany of the tools shared in this thread simplify working with CSV files, but only some allow running proper SQL queries.
SQLite, DuckDB and Clickhouse-local have been mentioned, but another very simple one, a single dependency-free binary, is https://github.com/multiprocessio/dsq
Not affiliated, just a happy user
In Using command line to process CSV files (2022)You can try this one too
https://github.com/multiprocessio/dsq
In Nushell.sh ls | where size > 10mb | sort-by modifiedWhat is the general opinion about Nushell and this tools (or others)?
https://github.com/multiprocessio/dsq
https://github.com/jqnatividad/qsv
https://csvkit.readthedocs.io/en/latest
https://github.com/kellyjonbrazil/jc
https://github.com/TomWright/dasel
https://github.com/johnkerl/miller
https://stedolan.github.io/jq
https://github.com/harelba/q
...
In Nushell.sh ls | where size > 10mb | sort-by modifiedWelcome to the gang! :)
https://github.com/multiprocessio/dsq#comparisons
Realistically though aside from the variety of input formats that DuckDB doesn't (yet) support, I think most people should probably use DuckDB or ClickHouse-local. Tools like dsq can provide broader support or a slightly simpler UX in some cases (and even that is obviously debatable). But I think the future is more the DuckDB or ClickHouse-local way.
dsq may end up being a frontend over DuckDB some day.
In DuckDB: Querying JSON files as if they were tablesdsq [0]
[0] - https://github.com/multiprocessio/dsq
In Ask HN: Programs that saved you 100 hours? (2022 edition)SPyQL is really cool and its design is very smart, with it being able to leverage normal Python functions!
As far as similar tools go, if you're interested, I recommend taking a look at DataFusion[0], dsq[1], and OctoSQL[2].
DataFusion is a very (very very) fast command-line SQL engine but with limited support for data formats.
dsq is based on SQLite which means it has to load data into SQLite first, but then gives you the whole breath of SQLite, it also supports many data formats, but is slower at the same time.
OctoSQL is faster, extensible through plugins, and supports incremental query execution, so you can i.e. calculate and display a running group by + count while tailing a log file. It also supports normal databases, not just file formats, so you can i.e. join with a Postgres table.
[0]: https://github.com/apache/arrow-datafusion
[
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1]: https://github.com/multiprocessio/dsq
[2]: https://github.com/cube2222/octosql
Disclaimer: Author of OctoSQL
> dsq registers go-sqlite3-stdlib so you get access to numerous statistics, url, math, string, and regexp functions that aren't part of the SQLite base. (https://github.com/multiprocessio/dsq#standard-library)
Ah, I wondered if they rolled their own SQL parser, but no, I now see the sqlite.go in the repo and all is made clear
In Jq Internals: Backtracking (2017)dsq works for me: https://github.com/multiprocessio/dsq
In Jq Internals: Backtracking (2017)I am currently evaluating dsq and its partner desktop app DataStation. AIUI, the developer of DataStation realised that it would be useful to extract the underlying pieces into a standalone CLI, so they both support the same range of sources.
dsq CLI - https://github.com/multiprocessio/dsq
DataStation desktop app - https://datastation.multiprocess.io/
Two alternative CLI tools that I looked at:
sq - https://sq.io/
octosql - https://github.com/cube2222/octosql
Honourable mentions to:
Miller - https://miller.readthedocs.io/en/latest/index.html
Dasel - https://daseldocs.tomwright.me/
These don't use SQL.
VisiData is also amazing for data navigation, although it requires some effort to get the model:
https://www.visidata.org/
In Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google SheetQ is a great project! Here's a comparison of Q against some of the other tools out there [0] (including dsq, which I wrote). And there's a benchmark in there too [1].
Whichever tool you end up using, I'm sure it will help out with your CLI data exploration!
[0] https://github.com/multiprocessio/dsq#comparisons
[1] https://github.com/multiprocessio/dsq#benchmark
In Q – Run SQL Directly on CSV or TSV FilesOctoSQL is an awesome project and Kuba has a lot of great experience to share from building this project I'm excited to learn from.
And while building a custom database engine does allow you to do pretty quick queries, there are a few issues.
First, the SQL implemented is nonstandard. As I was looking for documentation and it pointed me to `SELECT * FROM docs.functions fs`. I tried to count the number of functions but octosql crashed (a Go panic) when I ran `SELECT count(1) FROM docs.functions fs` and `SELECT count(*) FROM docs.functions fs` which is what I lazily do in standard SQL databases. (`SELECT count(fs.name) FROM docs.function fs` worked.)
This kind of thing will keep happening because this project just doesn't have as much resources today as SQLite, Postgres, DuckDB, etc. It will support a limited subset of SQL.
Second, the stan
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dard library seems pretty small. When I counted the builtin functions there were only 29. Now this is an easy thing to rectify over time but just noting about the state today.
And third this project only has builtin support for querying CSV and JSON files. Again this could be easy to rectify over time but just mentioning the state today.
octosql is a great project but there are also different ways to do the same thing.
I build dsq [0] which runs all queries through SQLite so it avoids point 1. It has access to SQLite's standard builtin functions plus a battery of extra statistic aggregation, string manipulation, url manipulation, date manipulation, hashing, and math functions custom built to help this kind of interactive querying developers commonly do [1].
And dsq supports not just CSV and JSON but parquet, excel, ODS, ORC, YAML, TSV, and Apache and nginx logs.
A downside to dsq is that it is slower for large files (say over 10GB) when you only want a few columns whereas octosql does better in some of those cases. I'm hoping to improve this over time by adding a SQL filtering frontend to dsq but in all cases dsq will ultimately use SQLite as the query engine.
You can find more info about similar projects in octosql's Benchmark section but I also have a comparison section in dsq [2] and an extension of the octosql benchmark with different set of tools [3] including duckdb.
Everyone should check out duckdb. :)
[0] https://github.com/multiprocessio/dsq
[1] https://github.com/multiprocessio/go-sqlite3-stdlib
[2] https://github.com/multiprocessio/dsq#comparisons
[3] https://github.com/multiprocessio/dsq#benchmark*
What's annoying about this is that the PR doesn't even say it's trying to run tests. It says everything is passing and just doesn't list the actions.
For a second I thought someone must have deleted the actions yaml files.
This is a dangerous failure mode.
https://github.com/multiprocessio/dsq/pull/82
Screenshot here: https://twitter.com/phil_eaton/status/1542168020516216832
In GitHub incident – now resolvedThis is a cool project! But if you just want a simple CLI, you can query Excel and ODS files with dsq [0]. It's the same end result without needing to carry plugins around and with support for many additional data formats. Plus a growing standard library of functions that don't come built into SQLite such as best-effort date parsing, URL parsing/extraction, statistical aggregation functions, math functions, string and regex helpers, hashing functions and so on [1].
An annoying thing about this extension-based style of file support is needing to create a new table for every new file if the schema is different. This is a limitation [2] of sqlite unfortunately. dsq doesn't work this way so it doesn't have that limit.
On the other hand, if you go this route you can more easily combine with other extensions. That's not really possible with dsq
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