Show HN: CSV GB+ by Data.olllo – Open and Process CSVs Locally
apps.microsoft.comI 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.
Thank you for this. I find myself increasingly using CSVs (TSVs actually) as the data format of choice. I confess I wish this was written for Mac too, but I like the trend of (once again) moving data processing down to our super computers on our desk...
QStudio allows querying CSV on mac via DuckDB: https://www.timestored.com/qstudio/csv-file-viewer I've been improving the Mac version a lot lately, key bindings, icon, an App package to download. So if you find any problems please raise a github issue.
… I‘m trying to use our super computers in our pockets, like an iPhone ;-) But still struggling with the way how to present CSV data effectively on a small screen, although it‘s huge in terms of pixels compared to computer screens from the 90s
It‘s interesting to research how capable applications like Lotus123 have been even on low resolutions like 800x600 pixel compared to today’s standard
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.
Is this better than the free Tad (https://www.tadviewer.com/) which seems to do similar things for free?
And on operating systems other than Windows...
It is 2025 and CSVs still dominate data interchange between organizations.
https://graydon2.dreamwidth.org/193447.html
parquet is also popular.
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I don't know if for Desktop App (most likely electron based) people expect any better.
As a point of comparison, I just downloaded the Windows binary for duckdb (which provides a nice TUI for similar tasks) and it was 9.84MB. People can and should expect better.