DB to CSV Converter: Free Online SQLite to CSV Tool, No Upload

How it works

• 1.Drop a .db file — it is read locally using sql.js (WebAssembly SQLite)
• 2.All tables appear with row and column counts
• 3.Select the tables you want — one table downloads as .csv, multiple as a .zip

Automatic date detection

SQLite stores dates as raw numbers or Julian day floats far more often than as readable text, which makes a straight CSV export full of columns like 1700000000 instead of a date anyone can read. This converter checks column names against common date-naming patterns (columns ending in _at, _on, or containing "date," "time," "timestamp," or "datetime") and, for matching columns, tries to detect whether the stored value is a Unix timestamp in seconds, a Unix timestamp in milliseconds, or a SQLite Julian day number. When it recognizes the format, it converts the value to a readable ISO date or timestamp in the exported CSV instead of leaving you with a raw integer to decode by hand.

Common use cases

Someone auditing an app's local storage pulls the underlying SQLite file from a device backup and converts its tables to CSV to review them in a spreadsheet without installing a database browser. A developer migrating data from an old SQLite-backed tool exports every table as CSV and imports each one into a new system, whether that's a different database or a spreadsheet- based tracker. A data analyst handed a raw .db export from an internal tool grabs just the two or three tables that matter, skipping the rest, and gets clean CSVs ready for a pivot table in minutes instead of setting up a local SQLite installation just to run a few SELECT statements.

Tips for clean exports

• •Check the row and column counts shown after loading. A table with zero rows still exports, but an empty CSV is a sign to double-check you picked the right file.
• •If a date column isn't recognized, it likely doesn't match the common naming patterns. It still exports as a raw value, just not auto-converted.
• •Exporting more than one table bundles them into a single ZIP so you don't end up juggling separate downloads for a dozen tables.
• •Fields containing commas, quotes, or line breaks are automatically quoted and escaped, so the CSV stays valid even for messy text columns.

Why SQLite instead of CSV in the first place

SQLite is the default storage format behind mobile app data, browser profiles, and countless lightweight tools precisely because a single file can hold many related tables with real data types, foreign keys, and indexes, something a folder of loose CSV files can't represent on its own. That structure is great for the application that created it and inconvenient for anyone who just wants to look at the data in a spreadsheet. CSV strips away the relationships between tables and the type information SQLite tracks internally, trading structure for the simplicity of rows and columns that Excel, Google Sheets, and virtually every data tool can open without installing anything.

Working with large or unfamiliar databases

When you drop in a database you didn't build yourself, the table list with row and column counts works as a quick map of what's inside before you commit to exporting anything. A table with millions of rows and a table with three rows both show up with their counts right away, so you can decide which ones are worth pulling into a spreadsheet and which ones you can skip. This matters more than it sounds like for real-world exports: mobile app databases in particular tend to include internal bookkeeping tables, like migration history or cache metadata, that clutter a ZIP export if you select everything without checking what's there first.