I used this a while back while running a waybackmachine style site for a large social media platform. I wanted to keep it simple with sqlite but when it got popular it started to become a problem. Marmot was the only thing that I was able to get to work with the amount of data I was pulling in. It would sync the master db from the main archiver server to all the ha servers so the user would be able to access it immediately no matter what ha server they got. The dev team was nice to talk to when I had some issues in setting it up.
It was definitively a weird backend setup I had made but it just worked once set up so I didnt have to touch any of the frontend code.
Author here! Every time I post my own stuff here it seems to sink, so hopefully this actually reaches some of you.
Marmot started as a sidecar project using triggers and polling to replicate changes over NATS. It worked, but I hit a wall pretty fast. Most people really want full ACID compliance and DDL replication across the cluster. I realized the only clean way to do that was to expose SQLite over a standard protocol.
While projects like rqlite use REST and others go the page-capture route, I decided to implement the MySQL protocol instead. It just makes the most sense for compatibility.
I’ve reached a point where it works with WordPress, which theoretically covers a huge chunk of the web. There are scripts in the repo to deploy a WP cluster running on top of Marmot. Any DB change replicates across the whole cluster, so you can finally scale WordPress out properly.
On the performance side, I’m seeing about 6K-7K inserts per second on my local machine with a 3-node quorum. It supports unix-sockets, and you can even have your processes read the SQLite DB file directly while routing writes through the MySQL interface. This gives you a lot of flexibility for read-heavy apps.
I know the "AI slop" label gets thrown around a lot lately, but I’ve been running this in production consistently. It’s taken a massive amount of manual hours to get the behavior exactly where it needs to be.
Just want to note that every time I see it I’m impressed with the project, great job so far.
The fact that you’ve been running this with WP is also a really huge use case/demonstration of trust in your different software — IMO this should be on the README prominently.
These days I personally just ignore projects that insist on MySQL — Postgres has won in my mind and is the better choice. The only way I’d run something like a WP hosting service is with a tool like Marmot.
One thing you might find interesting is trying marmot with something like Litestream v2 — marmot of course has its own replication system but I like the idea of having a backup system writing to s3. It seems trivial (as you’ve noted that you can still work directly on the s3 file) but would be a nice blog post/experiment to see “worked out” so to speak.(and probably wouldn't sink to the bottom of hn!)
Since Marmot pivoted to the MySQL wire protocol, I haven't had a clear picture of its advantages over using normal MySQL with active-active replication. Can you speak to that?
- Marmot let's you choose consistency level (ONE/QUORUM/FULL) vs MySQL's serializable.
- MySQL requires careful setup of replication, conflict avoidance and monitoring. Fencing split brain and failover is manual in many cases. Marmot even right now is easier to spin up, plus it's leaderless. So you can actually just have your client talk to different nodes (maybe in round robin fashion) to do load distribution.
- Marmot's eventual consistency + anti-entropy will recover brain-splits with you requiring to do anything. MySQL active active requires manual ops.
- Marmot's designed for read-heavy on the edge scenarios. Once I've completed the read-only replica system you can literally bring up or down lambda nodes with Marmot running as sidecar. With replicas being able to select DBs they want (WIP) you should be able to bring up region/org/scenario specific servers with their light weight copies, and writes will be proxied to main server. Applications are virtually unlimited. Since you can directly read SQLite database, think many small vector databases distributed to edge, or regional configurations, or catalogs.
Right now I've started off with full replication of every database in cluster. On my roadmap I have:
- Ability to launch a replica on selected databases from main cluster.
- Ability for replica to only download and replicate changes of select databases (right now all or nothing).
- Ability for replica to proxy DML & DDL into write cluster transparently.
- Custom set of commands for replicas to download and attach/detach databases on the fly.
This will instantly solve 80% of the problems for most of consumption today. I will probably go after on demand page stream and other stuff once core features are done.
Not to mention this solves majority use-cases of lambdas. One can have a persistent main cluster, and then lambda's coming up or going down on demand transparently.
- DDL gets really tricky in these cases, that's why you see Corrosion has this weird file based system.
- cr-sqlite ain't maintained anymore but I did some benchmarks and if I remember correctly it was as slow as 4x-8x depending upon type of your data & load. Storage bloats by 2x-3x, tombstones accumulate pretty fast as well.
I mean each mutation on every column looks something like:
Very helpful hearing about your own similar experiments with CRDTs. As a followup I'd be interested in more direct comparison between Marmot and Corrosion in terms of features/performance, since they both serve a similar use case and Corrosion seems to have worked through some of the CRDT issues you mentioned.
You might not, it depends on your use case. However SQLite is very small and lightweight, and amazing for read heavy databases. Using SQLite lets you bypass a lot of setup and configuration; then adding something like marmot lets you add being distributed after the fact.
Readit News
It was definitively a weird backend setup I had made but it just worked once set up so I didnt have to touch any of the frontend code.
Marmot started as a sidecar project using triggers and polling to replicate changes over NATS. It worked, but I hit a wall pretty fast. Most people really want full ACID compliance and DDL replication across the cluster. I realized the only clean way to do that was to expose SQLite over a standard protocol.
While projects like rqlite use REST and others go the page-capture route, I decided to implement the MySQL protocol instead. It just makes the most sense for compatibility.
I’ve reached a point where it works with WordPress, which theoretically covers a huge chunk of the web. There are scripts in the repo to deploy a WP cluster running on top of Marmot. Any DB change replicates across the whole cluster, so you can finally scale WordPress out properly.
On the performance side, I’m seeing about 6K-7K inserts per second on my local machine with a 3-node quorum. It supports unix-sockets, and you can even have your processes read the SQLite DB file directly while routing writes through the MySQL interface. This gives you a lot of flexibility for read-heavy apps.
I know the "AI slop" label gets thrown around a lot lately, but I’ve been running this in production consistently. It’s taken a massive amount of manual hours to get the behavior exactly where it needs to be.
The fact that you’ve been running this with WP is also a really huge use case/demonstration of trust in your different software — IMO this should be on the README prominently.
These days I personally just ignore projects that insist on MySQL — Postgres has won in my mind and is the better choice. The only way I’d run something like a WP hosting service is with a tool like Marmot.
One thing you might find interesting is trying marmot with something like Litestream v2 — marmot of course has its own replication system but I like the idea of having a backup system writing to s3. It seems trivial (as you’ve noted that you can still work directly on the s3 file) but would be a nice blog post/experiment to see “worked out” so to speak.(and probably wouldn't sink to the bottom of hn!)
- Marmot let's you choose consistency level (ONE/QUORUM/FULL) vs MySQL's serializable.
- MySQL requires careful setup of replication, conflict avoidance and monitoring. Fencing split brain and failover is manual in many cases. Marmot even right now is easier to spin up, plus it's leaderless. So you can actually just have your client talk to different nodes (maybe in round robin fashion) to do load distribution.
- Marmot's eventual consistency + anti-entropy will recover brain-splits with you requiring to do anything. MySQL active active requires manual ops.
- Marmot's designed for read-heavy on the edge scenarios. Once I've completed the read-only replica system you can literally bring up or down lambda nodes with Marmot running as sidecar. With replicas being able to select DBs they want (WIP) you should be able to bring up region/org/scenario specific servers with their light weight copies, and writes will be proxied to main server. Applications are virtually unlimited. Since you can directly read SQLite database, think many small vector databases distributed to edge, or regional configurations, or catalogs.
Now I'm curious how sharding/routing is handled- which seems like the final piece of the puzzle for scaling writes.
- Ability to launch a replica on selected databases from main cluster.
- Ability for replica to only download and replicate changes of select databases (right now all or nothing).
- Ability for replica to proxy DML & DDL into write cluster transparently.
- Custom set of commands for replicas to download and attach/detach databases on the fly.
This will instantly solve 80% of the problems for most of consumption today. I will probably go after on demand page stream and other stuff once core features are done.
Not to mention this solves majority use-cases of lambdas. One can have a persistent main cluster, and then lambda's coming up or going down on demand transparently.
- DDL gets really tricky in these cases, that's why you see Corrosion has this weird file based system. - cr-sqlite ain't maintained anymore but I did some benchmarks and if I remember correctly it was as slow as 4x-8x depending upon type of your data & load. Storage bloats by 2x-3x, tombstones accumulate pretty fast as well.
I mean each mutation on every column looks something like:
table, pk, cid, val, col_version, db_version, site_id, cl, seq
Overall I dropped the idea after spending month or two on it.
https://github.com/synopse/mORMot2
FreePascal ORM, so in an adjacent space (ORM, can work with both SQLite and MySQL).
I guess DB devs really love marmots? :-))