rqlite
marmot
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rqlite | marmot | |
---|---|---|
112 | 33 | |
14,835 | 1,621 | |
1.1% | - | |
9.9 | 8.6 | |
8 days ago | 3 months ago | |
Go | Go | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rqlite
- The lightweight, easy-to-use, distributed relational database built on SQLite
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CursusDB – A new scalable distributed document oriented database
Seems like you could do the same with rqlite [1], since SQLite supports JSON.
[1]: https://rqlite.io
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Rqlite 8.0
rqlite[1] creator here, happy to answer any questions about rqlite, this latest release, and how it works.
[1] https://rqlite.io
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Adding new database engine support
I found simple distributed RQlite https://github.com/rqlite/rqlite based on raft and sqlite. How hard is to add it?
- I'm All-In on Server-Side SQLite
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So, you want to deploy on the edge?
rqlite[1] creator here, happy to answer any questions. rqlite also supports read-only nodes, which can also help with reads at the "edge". It probably wouldn't scale to 100s of nodes, it is an option.
"rqlite supports adding read-only nodes. You can use this feature to add read scalability to the cluster if you need a high volume of reads, or want to distribute copies of the data nearer to clients – but don’t want those nodes counted towards the quorum. These types of nodes are also known as non-voting nodes."
[1] https://rqlite.io/
[2] https://rqlite.io/docs/clustering/read-only-nodes/
- LiteFS Cloud: Distributed SQLite with Managed Backups
- Show HN: Rqlite, distributed DB built on SQLite, now runs on MIPS, RISC, PowerPC
- rqlite v7.19.0: the lightweight distributed relational database built on Go, Raft, and SQLite -- now runs on MIPS, PowerPC, and RISC
- rqlite v7.18: the lightweight distributed database built on Go, Raft, and SQLite -- now with new Unified HTTP endpoint for easy reads and writes
marmot
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Distributed SQLite: Paradigm shift or hype?
If you're willing to accept eventual consistency (a big ask, but acceptable in some scenarios) then there are options like marmot [1] that replicate cdc over nats.
[1]: https://github.com/maxpert/marmot
- Marmot: Multi-writer distributed SQLite based on NATS
- Why you should probably be using SQLite
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The Raft Consensus Algorithm
I've written a whole SQLite replication system that works on top of RAFT ( https://github.com/maxpert/marmot ). Best part is RAFT has a well understood and strong library ecosystem as well. I started of with libraries and when I noticed I am reimplementing distributed streams, I just took off the shelf implementation (https://docs.nats.io/nats-concepts/jetstream) and embedded it in system. I love the simplicity and reasoning that comes with RAFT. However I am playing with epaxos these days (https://www.cs.cmu.edu/~dga/papers/epaxos-sosp2013.pdf), because then I can truly decentralize the implementation for truly masterless implementation. Right now I've added sharding mechanism on various streams so that in high load cases masters can be distributed across nodes too.
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SQLedge: Replicate Postgres to SQLite on the Edge
Very interesting! I have question ( out of my experience in https://github.com/maxpert/marmot ) how do get around the boot time, specially when a change log of table is pretty large in Postgres? I've implemented snapshotting mechanism in Marmot as part of quickly getting up to speed. At some level I wonder if we can just feed this PG replication log into NATS cluster and Marmot can just replicate it across the board.
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Show HN: Blueprint for a distributed multi-region IAM with Go and CockroachDB
One of the reasons I started writing Marmot (https://maxpert.github.io/marmot/) was for replicating bunch of tables across regions that were read heavy. I even used it for cache replication (because who cares if it’s a cache miss, but a hit will save me time and money). It’s hard to make such blue prints in early days of product, and by the time you hit a true growth almost everyone builds a custom solution for multi-region IAM.
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Stalwart All-in-One Mail Server (IMAP, JMAP, SMTP)
Amazing I was just looking for a good mail server to configure for my demo. Which reminds me since you folks have mentioned LiteStream, have you tried Marmot (https://github.com/maxpert/marmot); I recently configured Isso with Marmot to scale it out horizontally (https://maxpert.github.io/marmot/demo). I am super curious what kind of write workload on a sub thousand people organization will have and if Marmot can help scale it horizontally without Foundation DB. I always find the the convenience of SQLite amazing.
- Marmot: A distributed SQLite replicator built on top of NATS
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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?
dqlite - Embeddable, replicated and fault-tolerant SQL engine.
pocketbase - Open Source realtime backend in 1 file
litestream - Streaming replication for SQLite.
cr-sqlite - Convergent, Replicated SQLite. Multi-writer and CRDT support for SQLite
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
litefs - FUSE-based file system for replicating SQLite databases across a cluster of machines
bolt
wordpress-playground - Run WordPress in the browser via WebAssembly PHP
etcd - Distributed reliable key-value store for the most critical data of a distributed system [Moved to: https://github.com/etcd-io/etcd]
mssql-changefeed
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
sqlite3-preload - LD_PRELOAD hack to execute SQLite statements when an SQLite database is opened