dqlite VS boringproxy

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.

A couple of years ago I've read about this concept (already forgot the name) of using self hosted data storage with cloud applications. Basically, you as a user own your data and only permit the cloud hosted web application to access it - not own it and manage in your place.

I was thinking of a similar concept, but in the context of mobile applications. The mobile application itself would be accessible via Google Play Store/App Store, but the backend part would be self hosted and upon opening the application you would have to specify how to access backend.

My question is how would I access the backend if it was hosted on let's say rpi running in the living room? It's not a problem as long as I'm within the home network, but I want seemless network transition without losing access when entering/leaving the house. I was told https://www.cloudflare.com/en-gb/products/zero-trust/access/ could be used for this, but to me it sounds a bit of an overkill to use it for an application which would never be used by more than a single digit amount of users. This looks more suitable: https://github.com/boringproxy/boringproxy

Finally, someone in the above project's Matrix room directed me towards boringproxy - https://github.com/boringproxy/boringproxy. This was the perfect solution. No lengthy config files, easy to use and automate. Setup took about an hour and now everything is back up and running. The only issue I've currently not been able to solve is one where the container seems to use a websocket, which keeps getting timed out (will investigate this further tomorrow).

boringproxy (GitHub) is my go-to for this sort of thing. Thanks for the announcement, I'll have to do a head-to-head and see how they stack up!

boringproxy

Am I the only one who thinks SQLite is still too complicated for many programs? Maybe it's just the particular type of software I normally work on, which tends towards small, self-hosted networking services[0] that would often have a single user, or maybe federated with <100 users. These programs need a small amount of state for things like tokens, users accounts, and maybe a bit of domain-specific things. This can all live in memory, but needs to be persisted to disk on writes. I've reached for SQLite several times, and always come back to just keeping a struct of hashmaps[1] in memory and dumping JSON to disk. It's worked great for my needs.

Now obviously if I wanted to scale up, at some point you would have too many users to fit in memory. But do programs at that scale actually need to exist? Why can't everyone be on a federated server with state that fits in memory/JSON? I guess that's more of a philosophical question about big tech. But I think it's interesting that most of our tech stack choices are driven by projects designed to work at a scale most of us will never need, and maybe nobody needs.

[0]: https://boringproxy.io/

[1]: https://github.com/boringproxy/boringproxy/blob/master/datab...

This is the commit that seems to have broken the docker image.

I use https://github.com/boringproxy/boringproxy