Export SQLite to CSV
Any table, any
query.
Free SQLite to CSV converter. Upload any .db or .sqlite file — all tables are detected automatically. Select a table or write a custom SQL query. Download CSV or copy to clipboard. Your database never leaves your browser.
Faster alternatives when you have the sqlite3 CLI or Python available.
sql.js loads the SQLite 3 WebAssembly engine and reads your .db file as an ArrayBuffer. It parses the SQLite binary format and gives you a full in-memory database with the complete schema and data intact.
CSVShift queries sqlite_master to list all tables with their row counts. Selecting a table auto-fills the query as SELECT * FROM "table"; — edit to add WHERE, JOINs or aggregates.
The query runs against the in-memory database. Results are serialised to RFC 4180 CSV with UTF-8 BOM encoding — ready to open in Excel, Google Sheets, or re-import into any database tool.
iOS and Android apps store data in SQLite databases. Exporting tables as CSV is the standard way to analyse or back up app data without special tools.
Chrome, Firefox and Safari store history, bookmarks and downloads in SQLite databases. Exporting to CSV lets you analyse browsing patterns or migrate data.
Moving data from SQLite to MySQL, PostgreSQL or a cloud service requires exporting to CSV first. Custom query support lets you select specific columns and filter rows before migration.
SQLite databases from data pipelines, IoT devices and embedded systems often need to be analysed in Excel or Google Sheets. Exporting tables to CSV is the fastest path from binary .db to a shareable spreadsheet.
Binary .db read
in your browser. No server.
CSVShift opens SQLite databases using sql.js — SQLite 3 compiled to WebAssembly. Your .db file is read as an ArrayBuffer in your browser tab. The binary SQLite format is parsed locally without any data leaving your device.
import sqlite3, pandas as pd; df = pd.read_sql('SELECT * FROM table', sqlite3.connect('db.sqlite')); df.to_csv('out.csv', index=False).sqlite3 -header -csv database.db "SELECT * FROM table;" > output.csv — works on macOS, Linux and Windows.