sql.js VS dqlite

Hi HN! A friend and I were inspired by projects like https://github.com/sql-js/sql.js and the idea of querying files served over CDN with HTTP range requests. We started thinking: what would a database that was specifically designed for this type of use case look like? So we started building one, and we landed on a functional prototype that we're pretty proud of!

With our prototype, Appendable, we're able to serve and query large (GB+) datasets by hosting them on a static file host like Amazon S3 or Cloudflare R2 without running a separate server and worrying about things like tail latency, replication, and connection pooling -- all that is handled for us by the file hoster.

Additionally, one tenet that we have been following is Appendable won't touch your underlying data, so your jsonl file is preserved and we point at that data instead of consuming it into an Appendable-specific file format. This keeps your data yours and makes it easy to introspect the data: just open it up with your favorite editor aka vim.

We're curious what you think, we're excited to build this out further to get the performance even better and add features like pubsub. Everything is open source at https://github.com/kevmo314/appendable.

Kevin and Matthew

My project is powered by sql.js, I recommend checking that out if you're interested - https://github.com/sql-js/sql.js/

Maybe you can try to use some SQL database compiled as Web Assembly Modules? Like this one for example: https://github.com/sql-js/sql.js

If you want to have persistence, then I would go with a database like Dexie, as it uses IndexedDB and has transactions. If you just want something that's in memory, you could look at Sql.js or something simple like lowdb.

not necessarily. you can host an html/js/sqlite site on github pages for free. json -> sqlite3 js -> sql

Link: https://sql.js.org

Does it work with really large files? Like, >100mb or so. I was considering making something similar but with sqlite.js [1], but the problem with it is that it loads everything in memory, so I wasn't entirely sure how it will deal with larger workloads.

[1]: https://sql.js.org/#/

If you're interested in this, here are some related projects that all take slightly different approaches:

- LiteSync directly competes with Marmot and supports DDL sync, but is closed source commercial (similar to SQLite EE): https://litesync.io

- dqlite is Canonical's distributed SQLite that depends on c-raft and kernel-level async I/O: https://dqlite.io

- cr-sqlite is a Rust-based loadable extension that adds CRDT changeset generation and reconciliation to SQLite: https://github.com/vlcn-io/cr-sqlite

Slightly related but not really (no multi writer, no C-level SQLite API or other restrictions):

- comdb2 (Bloombergs multi-homed RDMS using SQLite as the frontend)

- rqlite: RDMS with HTTP API and SQLite as the storage engine, used for replication and strong consistency (does not scale writes)

- litestream/LiteFS: disaster recovery replication

- liteserver: active read-only replication (predecessor of LiteSync)

I'd be curious for a similar tuning with Dqlite: https://github.com/canonical/dqlite

Anyone knows how the DB this is about, https://rqlite.io/, compares with https://dqlite.io/ by Canonical (both seem to be distributed versions of sqlite)?

For folks' context, the new tool that's being discussed in the thread mentioned by the parent here is litefs [0], as well as which you can also look at rqlite [1] and dqlite [2], which all provide different trade-offs (e.g. rqlite is 'more strongly consistent' than litefs).

[0]: https://github.com/superfly/litefs

[1]: https://github.com/rqlite/rqlite

[2]: https://github.com/canonical/dqlite

I presume you're familiar with https://github.com/canonical/dqlite (made by my employer) and https://github.com/rqlite/rqlite (unrelated)? How will mvsqlite compare to those?

Check out dqlite, it's sqlite but with a raft consensus to distribute changes through a log: https://dqlite.io/ You can link it in as a library too, it sounds like exactly what you want.