Software Alternatives, Accelerators & Startups

OctoSQL VS Tidy Viewer

Compare OctoSQL VS Tidy Viewer and see what are their differences

OctoSQL logo OctoSQL

OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL. - cube2222/octosql

Tidy Viewer logo Tidy Viewer

Tidy Viewer is a cross-platform CLI csv pretty printer that uses column styling to maximize viewer enjoyment.
  • OctoSQL Landing page
    Landing page //
    2023-08-26
  • Tidy Viewer Landing page
    Landing page //
    2023-08-23

Category Popularity

0-100% (relative to OctoSQL and Tidy Viewer)
Databases
100 100%
0% 0
Linux
0 0%
100% 100
Big Data
100 100%
0% 0
CSV Editors
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, OctoSQL seems to be a lot more popular than Tidy Viewer. While we know about 22 links to OctoSQL, we've tracked only 2 mentions of Tidy Viewer. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

OctoSQL mentions (22)

  • Analyzing multi-gigabyte JSON files locally
    OctoSQL[0] or DuckDB[1] will most likely be much simpler, while going through 10 GB of JSON in a couple seconds at most. Disclaimer: author of OctoSQL [0]: https://github.com/cube2222/octosql. - Source: Hacker News / over 1 year ago
  • DuckDB: Querying JSON files as if they were tables
    This is really cool! With their Postgres scanner[0] you can now easily query multiple datasources using SQL and join between them (i.e. Postgres table with JSON file). Something I strived to build with OctoSQL[1] before. It's amazing to see how quickly DuckDB is adding new features. Not a huge fan of C++, which is right now used for authoring extensions, it'd be really cool if somebody implemented a Rust extension... - Source: Hacker News / over 1 year ago
  • Show HN: ClickHouse-local – a small tool for serverless data analytics
    Congrats on the Show HN! It's great to see more tools in this area (querying data from various sources in-place) and the Lambda use case is a really cool idea! I've recently done a bunch of benchmarking, including ClickHouse Local and the usage was straightforward, with everything working as it's supposed to. Just to comment on the performance area though, one area I think ClickHouse could still possibly improve... - Source: Hacker News / over 1 year ago
  • Command-line data analytics made easy
    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... - Source: Hacker News / over 1 year ago
  • Steampipe – Select * from Cloud;
    To add somewhat of a counterpoint to the other response, I've tried the Steampipe CSV plugin and got 50x slower performance vs OctoSQL[0], which is itself 5x slower than something like DataFusion[1]. The CSV plugin doesn't contact any external API's so it should be a good benchmark of the plugin architecture, though it might just not be optimized yet. That said, I don't imagine this ever being a bottleneck for the... - Source: Hacker News / over 1 year ago
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Tidy Viewer mentions (2)

What are some alternatives?

When comparing OctoSQL and Tidy Viewer, you can also consider the following products

LNAV - The Log File Navigator (lnav) is an advanced log file viewer for the console.

CSVFileView - CSV/Tab-delimited file viewer and converter for Windows

DuckDB - DuckDB is an in-process SQL OLAP database management system

Tad - Create sleeve and cover art for your band in minutes

Materialize - A Streaming Database for Real-Time Applications

CSV Quick Viewer - Windows file viewer for delimited text files like CSV or Tab delimited files.