little-raft
raft
| little-raft | raft | |
|---|---|---|
| 7 | 7 | |
| 404 | 7,860 | |
| - | 0.9% | |
| 0.0 | 6.0 | |
| over 1 year ago | 6 days ago | |
| Rust | Go | |
| MIT License | Mozilla Public License 2.0 |
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.
little-raft
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Show /r/rust: Viewstamped Replication for Rust
My perspective is that VSR seems much more easier to grasp than Raft based on reading and contributing to Ilya Andreev's Little Raft. The selection of primary replica ("leader election" in Raft), for example, is dead-simple in VSR (you maintain a deterministic order of nodes and round-robin). Also, VSR seems to do a better job at decoupling the different scenarios at protocol level (backup fell behind, crashed, etc.) whereas in Raft the AppendEntries is a big hammer that does everything. I have very little experience on Paxos so can't really compare it to VSR.
- Show HN: I implemented Raft in Rust in under 1k lines
- Raft Consensus Protocol
- Side Project: Raft distributed consensus algorithm implementation & CLI visualization in Rust
- Show HN: I Made a Raft Implementation and CLI Visualization in Rust
- Side project: Raft distributed consensus algorithm implementation & CLI visualization in Rust
raft
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Leader election library
Depending on your exact needs, you could try HashiCorp's Raft implementation: https://github.com/hashicorp/raft
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Implementing a distributed key-value store on top of implementing Raft in Go
I have found the performance tests very tricky to get to pass without having any input from others. The assignment is really very unforgiving, I would wager the test suite is comparable to how commercial Raft implementations are tested (e.g. https://github.com/hashicorp/raft)
- Raft Is So Fetch: The Raft Consensus Algorithm Explained Through Mean Girls
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Concurrency in Go is hard
While searching on GitHub, I found a pull request in the Raft implementation by Hashicorp (a distributed consensus algorithm), which we can use to demonstrate the following problem. Let’s start by showing the code (at api.go):
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Looking for a TypeScript Implementation of Raft
Hey,
you could inspire yourself by hashicorps raft implementation written in go and build one for typescript. Code is quite good to read and Go ins't that far away from typescript.
https://github.com/hashicorp/raft
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rqlite, the light distributed database built with Go and SQLite, v7.2 now with autoclustering via DNS and DNS SRV
Production-grade distributed consensus system.
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Raft Consensus Protocol
In general Hashicorp's repos are high quality:
https://github.com/hashicorp/raft
Example application: https://github.com/Jille/raft-grpc-example
What are some alternatives?
riteraft - RiteRaft - A raft framework, for regular people
serf - Service orchestration and management tool.
raft-grpc-example - Example code for how to get hashicorp/raft running with gRPC
tendermint - ⟁ Tendermint Core (BFT Consensus) in Go
tigerbeetle - A distributed financial accounting database designed for mission critical safety and performance. [Moved to: https://github.com/tigerbeetledb/tigerbeetle]
torrent - Full-featured BitTorrent client package and utilities
uppercut - Small and simple actor model implementation.
etcd - Distributed reliable key-value store for the most critical data of a distributed system [Moved to: https://github.com/etcd-io/etcd]
ruaft - Raft implemented in Rust
dragonboat - A feature complete and high performance multi-group Raft library in Go.
politeia-rs - Decred Politeia in Rust
DHT - BitTorrent DHT Protocol && DHT Spider.