donutdb
sqlite-y-crdt
donutdb | sqlite-y-crdt | |
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4 | 1 | |
163 | 10 | |
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5.3 | 4.5 | |
10 months ago | 4 months ago | |
Go | Rust | |
MIT License | MIT License |
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donutdb
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LiteFS Cloud: Distributed SQLite with Managed Backups
Man this is cool. While I really enjoy my own solution of using a custom SQLite vfs that stores your db transparently in dynamodb[0], this really is a compelling alternative.
I wonder how viable this would be to use from aws lambda? It seems like the way lambda does concurrency probably doesn't play all that well with litefs. Maybe it's time to move some workloads over to fly.io.
[0]: https://github.com/psanford/donutdb
- DonutDB: DynamoDB-Backed SQLite Databases
- DonutDB: A SQL database implemented on DynamoDB and SQLite
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Ask HN: What could a modern database do that PostgreSQL and MySQL can't
There's a bunch of projects that have implemented this. I wrote a SQLite VFS in Go that lets you query a read-only SQLite db over http (including from s3) [0].
The VFS API offers the possibility for weirder storage solutions, if thats the type of thing you're into. Recently I've been moving some of my personal websites hosted on AWS Lambda over to use a read/write sqlite db backed by DynamoDB[1]. There are a bunch of limitations to this type of thing (like it uses a global write lock), but it works nicely for DBs that have low write frequency.
[0]: https://github.com/psanford/sqlite3vfshttp
[1]: https://github.com/psanford/donutdb
sqlite-y-crdt
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LiteFS Cloud: Distributed SQLite with Managed Backups
Great that you brought it up. I will fill in the perspective of what I am doing for solving this in Marmot (https://github.com/maxpert/marmot). Today Marmot already records changes via installing triggers to record changes of a table, hence all the offline changes (while Marmot is not running) are never lost. Today when Marmot comes up after a long offline (depending upon max_log_size configuration), it realizes that and tries to catch up changes via restoring a snapshot and then applying rest of logs from NATS (JetStream) change logs. I am working on change that will be publishing those change logs to NATS before it restores snapshots, and once it reapplies those changes after restoring snapshot everyone will have your changes + your DB will be up to date. Now in this case one of the things that bothers people is the fact that if two nodes coming up with conflicting rows the last writer wins.
For that I am also exploring on SQLite-Y-CRDT (https://github.com/maxpert/sqlite-y-crdt) which can help me treat each row as document, and then try to merge them. I personally think CRDT gets harder to reason sometimes, and might not be explainable to an entry level developers. Usually when something is hard to reason and explain, I prefer sticking to simplicity. People IMO will be much more comfortable knowing they can't use auto incrementing IDs for particular tables (because two independent nodes can increment counter to same values) vs here is a magical way to merge that will mess up your data.
What are some alternatives?
absurd-sql - sqlite3 in ur indexeddb (hopefully a better backend soon)
sqld - LibSQL with extended capabilities like HTTP protocol, replication, and more.
lovefield - Lovefield is a relational database for web apps. Written in JavaScript, works cross-browser. Provides SQL-like APIs that are fast, safe, and easy to use.
litestack
sqlite3vfshttp - Go sqlite3 http vfs: query sqlite databases over http with range headers
mycelite - Mycelite is a SQLite extension that allows you to synchronize changes from one instance of SQLite to another.
stolon - PostgreSQL cloud native High Availability and more.
marmot - A distributed SQLite replicator built on top of NATS
mysql-live-select - NPM Package to provide events on updated MySQL SELECT result sets
meteor-mysql - Reactive MySQL for Meteor