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Zsv Alternatives
Similar projects and alternatives to zsv
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Kargo
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AppSignal
Monitoring that respects your time & budget. APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.
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Ditto
Ditto is an extension to the Windows Clipboard. You copy something to the Clipboard and Ditto takes what you copied and stores it in a database to retrieve at a later time.
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simdjson
Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
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miller
Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
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dasel
Unified querying, transformation, and modification of JSON, TOML, YAML, XML, INI, HCL, KDL and CSV.
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octosql
OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.
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tidy-viewer
📺(tv) Tidy Viewer is a cross-platform CLI csv pretty printer that uses column styling to maximize viewer enjoyment.
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tsv-utils
eBay's TSV Utilities: Command line tools for large, tabular data files. Filtering, statistics, sampling, joins and more.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better zsv alternative or higher similarity.
zsv discussion
zsv reviews and mentions
Posts with mentions or reviews of zsv.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2025-12-07.
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Ruby CSV Parsing 5-6x Faster
I wrapped zsv, a SIMD-accelerated CSV parser written in C, into a Ruby gem. SIMD means it uses special CPU instructions to process multiple bytes at once - the same tech that makes video encoding and game physics fast.
- Show HN: ZSV – A fast, SIMD-based CSV parser and CLI toolkit
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How fast can you parse a CSV file in C#?
Haven't yet seen any of these beat https://github.com/liquidaty/zsv when real-world constraints are applied (e.g. we no longer assume that line ends are always \n, or that there are no dbl-quote chars, embedded commas/newlines/dbl-quotes). And maybe under the artificial conditions as well.
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CSVs Are Kinda Bad. DSVs Are Kinda Good
I cannot imagine any way it is worth anyone's time to follow this article's suggestion vs just using something like zsv (https://github.com/liquidaty/zsv, which I'm an author of) or xsv (https://github.com/BurntSushi/xsv/edit/master/README.md) and then spending that time saved on "real" work
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Analyzing multi-gigabyte JSON files locally
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...
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
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
- Yq is a portable yq: command-line YAML, JSON, XML, CSV and properties processor
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csvkit: Command-line tools for working with CSV
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):
---
- Ask HN: Programs that saved you 100 hours? (2022 edition)
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Show HN: Split CSV into multiple files to avoid the Excel's 1M row limitation
}
```
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)
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www.saashub.com | 13 Sep 2026
Stats
Basic zsv repo stats
29
397
9.0
4 days ago
liquidaty/zsv is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of zsv is C.
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