

Delimited
Delimited is a minimalistic CSV and TSV editor for macOS. It’s built for speed and simplicity, letting you quickly create or explore tables and save them in either CSV or TSV format.
Features
Properties
- Lightweight
- Privacy focused
- Minimalistic
Features
- No Tracking
- Works Offline
- Ad-free
- No registration required
- Dark Mode
- Swift
- Native application
Tags
- rfc-4180
- tsv
- CSV Viewer
Delimited News & Activities
Recent News
Recent activities
- thinks No Tracking is a important feature of Delimited
- lido2627 liked Delimited
POX added Delimited as alternative to EmEditor, Modern CSV, Rons Data Edit and CSVboard- POX added Delimited
Delimited information
What is Delimited?
Delimited is a minimalistic CSV and TSV editor for macOS. It’s built for speed and simplicity, letting you quickly create or explore tables and save them in either CSV or TSV format. To ensure compatibility with other tools files adhere strictly to the RFC 4180 specification. Lightweight, straightforward and (reasonably) fast, specifically made for working with CSV files. Delimited is native, built in Swift, and designed to handle everything from small to large tables. While it’s not focused on excelling in any particular benchmark, it strikes a balance between performance, design and user experience.
Delimited keeps its feature set deliberately limited. Files with the .csv extension use commas as delimiters, while .tsv files use tabs—other delimiters aren’t supported to maintain compatibility with RFC 4180. You can choose whether the first row is treated as a header or regular data.
All rows and columns are displayed in a single scrollable view, making it easy to explore your table. Add, move, or remove rows and columns as needed. Fields with newlines expand within a single cell, while clipped text can be revealed by hovering over the cell. A toggleable subtitle provides extra context, like table dimensions, selected rows or columns, or the currently active cell. Copying and pasting is plain-text only, perfect for creating quick subsets of your data.







