Dsq Alternatives

dsq reviews and mentions

• Ask HN: Programs that saved you 100 hours? (2022 edition)
  69 projects | news.ycombinator.com | 20 Dec 2022
• Command-line data analytics made easy
  6 projects | news.ycombinator.com | 3 Nov 2022

  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, 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 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

  [1]: https://github.com/multiprocessio/dsq

  [2]: https://github.com/cube2222/octosql

  Disclaimer: Author of OctoSQL

• Jq Internals: Backtracking
  10 projects | news.ycombinator.com | 5 Oct 2022

  > 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

• Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google Sheet
  9 projects | news.ycombinator.com | 24 Sep 2022

  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

• OctoSQL allows you to join data from different sources using SQL
  13 projects | news.ycombinator.com | 14 Jul 2022

  OctoSQL 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 standard 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

• GitHub Actions are down again
  2 projects | news.ycombinator.com | 29 Jun 2022

  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

• Xlite: Query Excel, Open Document spreadsheets (.ods) as SQLite virtual tables
  6 projects | news.ycombinator.com | 25 Jun 2022

  This is a cool project! But if you query Excel and ODS files with dsq you get the same thing 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].

  [0] https://github.com/multiprocessio/dsq

  [1] https://github.com/multiprocessio/go-sqlite3-stdlib

• Do org tables have a means of filtering the records by some column value?
  3 projects | reddit.com/r/emacs | 29 May 2022

  ob-dsq gives org source block support for the command line tool dsq. This lets you query an org-mode table with SQL. So that's good if you know SQL. And is more powerful than just simple column filtering.

• Lies we tell ourselves to keep using Golang
  7 projects | news.ycombinator.com | 29 Apr 2022

  I use Go heavily cross-platform developing DataStation [0] and dsq [1]. I am not an expert. And I don't have proof for it but on some rudimentary benchmarks the Linux-specific file idioms in the Go standard library definitely don't seem to translate well to even macOS let alone Windows. For example some good streaming techniques for reading large files on Linux that work really well there seemed to be pretty bad on macOS.

  I think Amos has presented more proof than I can on the topic of just how Linux-influenced Go is. And I think it is fine for the majority of Go users because the majority users of Go are building server apps or Linux CLIs.

  Amos has spent some time building cross-platform desktop systems with Go for itch.io and I think I'm seeing some of the same things they are in that scenario.

  I think this is a reasonable article. If Amos gets flame-y at any point I think it's worth ignoring because there does seem to be something up with Go in cross-platform applications.

  I like Go a lot and for most things I'd keep using it still. Just sharing some observations.

  [0] https://github.com/multiprocessio/datastation

  [1] https://github.com/multiprocessio/dsq

• Zq: An Easier (and Faster) Alternative to Jq
  36 projects | news.ycombinator.com | 26 Apr 2022
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