steampipe VS zsv

Steampipe is a tool for querying cloud APIs and other data sources using SQL in a zero-ETL manner.

Readers may also enjoy Steampipe [1], an open source CLI to live query Google Sheets [2] and 140+ other services with SQL (e.g. AWS, GitHub, etc). It uses Postgres Foreign Data Wrappers under the hood and supports joins etc across the services. (Disclaimer - I'm a lead on the project.)

1 - https://github.com/turbot/steampipe

be mindful of its AGPLv3 https://github.com/turbot/steampipe/blob/v0.21.8/LICENSE (AFAIK v0.4.3 is the last MIT release https://github.com/turbot/steampipe/blob/v0.4.3/LICENSE ) and the actual providers are Apache 2 <https://github.com/turbot/steampipe-plugin-aws/blob/v0.131.0...> (but I don't know if provider drift makes them compatible with 0.4 or not)

iasql seems to be AWS only, but good for them for taking this on:

In a prior post I showed how to install Steampipe in AWS CloudShell to instantly query over 460+ resource types from your AWS APIs using SQL, and another post on how to use the Steampipe AWS Compliance mod to assess over 25+ security benchmarks across your AWS accounts.

Readers may find Steampipe's [1] AWS Thrifty Mod [2] useful. It will automatically scan multiple accounts and regions for 50 cost saving opportunities - many of which are looking for over-provisioned or unused resources. For example, it's crazy how much you can save by doing things like just converting your EBS volumes to the newer gp3 type. Combine with Flowpipe [3] to automate checks and actions. It's all open source and extensible.

1 - https://github.com/turbot/steampipe

Steampipe [1] is an open source project [2] that includes an embedded Postgres to instantly query cloud, code & more with SQL. This release expands our plugin ecosystem [3] to be a full Zero-ETL platform. Steampipe plugins can now run natively in your own Postgres as Foreign Data Wrappers [4], as SQLite extensions [5] or as simple data export tools [6]. Please give it a try, we'd love your feedback and contributions!

1 - https://steampipe.io

If it could be tabular in nature, maybe convert to sqlite3 so you can make use of indexing, or CSV to make use of high-performance tools like xsv or zsv (the latter of which I'm an author).

https://github.com/BurntSushi/xsv

https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...

Parsing CSV doesn't have to be slow if you use something like xsv or zsv (https://github.com/liquidaty/zsv) (disclaimer: I'm an author). The speed of CSV parsers is fast enough that unless you are doing something ultra-trivial such as "count rows", your bottleneck will be elsewhere.

The benefits of CSV are:

- human readable

- does not need to be typed (sometimes, data in the raw such as date-formatted data is not amenable to typing without introducing a pre-processing layer that gets you further from the original data)

- accessible to anyone: you don't need to be a data person to dbl-click and open in Excel or similar

The main drawback is that if your data is already typed, CSV does not communicate what the type is. You can alleviate this through various approaches such as is described at https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql..., though I wouldn't disagree that if you can be assured that your starting data conforms to non-text data types, there are probably better formats than CSV.

The main benefit of Arrow, IMHO, is less as a format for transmitting / communicating but rather as a format for data at rest, that would benefit from having higher performance column-based read and compression

I wanted so much to use csvkit and all the features it had, but its horrendous performance made it unscalable and therefore the more I used it, the more technical debt I accumulated.

This was one of the reasons I wrote zsv (https://github.com/liquidaty/zsv). Maybe csvkit could incorporate the zsv engine and we could get the best of both worlds?

Examples (using majestic million csv):

---

}

```

This of course assumes that each line is a single record, so you'll need some preprocessing if your CSV might contain embedded line-ends. For the preprocessing, you can use something like the `2tsv` command of https://github.com/liquidaty/zsv (disclaimer: I'm its author), which converts CSV to TSV and replaces newline with \n.

You can also use something like `xsv split` (see https://lib.rs/crates/xsv) which frankly is probably your best option as of today (though zsv will be getting its own shard command soon)

Am looking for one-time help creating documentation (e.g. man pages, tutorials) for open source project (e.g. https://github.com/liquidaty/zsv) as well as product documentation for commercial products, but not enough need for a full-time job. Requires familiarity with, for lack of better term, data janitorial work, and preferably with methods of auto-generating documentation. Any suggestions as to forums or other ways to find folks who might fit the bill for ad-hoc or part-time work of this nature?

Nice work. I am a fan of tools like this and look forward to giving this a try.

However, in my first attempted query (version 3.1.6 on MacOS), I ran into significant performance limitations and more importantly, it did not give correct output.

In particular, running on a narrow table with 1mm rows (the same one used in the xsv examples) using the command "select country, count() from worldcitiespop_mil.csv group by country" takes 12 seconds just to get an incorrect error 'no such column: country'.

using sqlite3, it takes two seconds or so to load, and less than a second to run, and gives me the correct result.

Using https://github.com/liquidaty/zsv (disclaimer, I'm one of its authors), I get the correct results in 0.95 seconds with the one-liner `zsv sql 'select country, count() from data group by country' worldcitiespop_mil.csv`.

I look forward to trying it again sometime soon

All this banter arguing over CSV, JSON, sqlite seems unnecessary when you can just push format X through a pipe and get whichever format Y you want back out: https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...

(disclaimer: I'm one of the zsv authors)