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Show HN: CSV GB+ by Data.olllo – Open and Process CSVs Locally

(apps.microsoft.com)
51 points olllo | 1 comments | 14 May 25 15:12 UTC | HN request time: 0.329s | source

I built CSV GB+ by Data.olllo, a local data tool that lets you open, clean, and export gigabyte-sized CSVs (even billions of rows) without writing code.

Most spreadsheet apps choke on big files. Coding in pandas or Polars works—but not everyone wants to write scripts just to filter or merge CSVs. CSV GB+ gives you a fast, point-and-click interface built on dual backends (memory-optimized or disk-backed) so you can process huge datasets offline.

Key Features: Handles massive CSVs with ease — merge, split, dedup, filter, batch export

Smart engine switch: disk-based "V Core" or RAM-based "P Core"

All processing is offline – no data upload or telemetry

Supports CSV, XLSX, JSON, DBF, Parquet and more

Designed for data pros, students, and privacy-conscious users

Register for 7-days free to pro try, pro versions remove row limits and unlock full features. I’m a solo dev building Data.olllo as a serious alternative to heavy coding or bloated enterprise tools.

Download for Windows: https://apps.microsoft.com/detail/9PFR86LCQPGS

User Guide: https://olllo.top/articles/article-0-Data.olllo-UserGuide

Would love feedback! I’m actively improving it based on real use cases.

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paddy_m ◴[14 May 25 16:22 UTC] No.43986366[source]▶
Do you have a demo video?

What are you using for processing (polars)?

Marketing note: I'm sure you're proud of P Core/V Core, but that doesn't matter to your users, it's an implementation detail. At a maximum I'd write "intelligent execution that scales from small files to large files".

As an implementation note, I would make it simple to operate on just the first 1000 (10k or 100k) rows so responses are super quick, then once the users are happy about the transform, make it a single click to operate on the entire file with a time estimate.

Another feature I'd like in this vein is execute on a small subset, then if you find an error with a larger subset, try to reduce the larger subset to a small quick to reproduce version. Especially for deduping.

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1. ◴[14 May 25 18:54 UTC] No.43988003[source]▶