A faster way to copy SQLite databases between computers

Summary

A faster way to copy SQLite databases between computers I store a lot of data in SQLite databases on remote servers, and I often want to copy them to my local machine for analysis or backup. When I’m starting a new project and the database is near-empty, this is a simple rsync operation: $ rsync --progress username@server:my_remote_database.db my_local_database.db As the project matures and the database grows, this gets slower and less reliable. Downloading a 250MB database from my web server takes about a minute over my home Internet connection, and that’s pretty small – most of my databases are multiple gigabytes in size. I’ve been trying to make these copies go faster, and I recently discovered a neat trick. What really slows me down is my indexes. I have a lot of indexes in my SQLite databases, which dramatically speed up my queries, but also make the database file larger and slower to copy. (In one database, there’s an index which single-handedly accounts for half the size on disk!) The indexes don’t store anything unique – they just duplicate data from other tables to make queries faster. Copying the indexes makes the transfer less efficient, because I’m copying the same data multiple times. I was thinking about ways to skip copying the indexes, and I realised that SQLite has built-in tools to make this easy. Dumping a database as a text file SQLite allows you to dump a database as a text file. If you use the .dump command, it prints the entire database as a series of SQL statements. This text file can often be significantly smaller than the original database. Here’s the command: $ sqlite3 my_database.db .dump > my_database.db.txt And here’s what the beginning of that file looks like: PRAGMA foreign_keys=OFF; BEGIN TRANSACTION; CREATE TABLE IF NOT EXISTS "tags" ( [name] TEXT PRIMARY KEY, [count_uses] INTEGER NOT NULL ); INSERT INTO tags VALUES('carving',260); INSERT INTO tags VALUES('grass',743); … Crucially, this reduces the large and disk-heavy indexes into ...