async raft
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[](https://crates.io/crates/async-raft)
[](https://docs.rs/async-raft)
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Blazing fast Rust, a modern consensus protocol, and a reliable async runtime — this project intends to provide a consensus backbone for the next generation of distributed data storage systems (SQL, NoSQL, KV, Streaming, Graph ... or maybe something more exotic).
[The guide](https://async-raft.github.io/async-raft) is the best place to get started, followed by [the docs](https://docs.rs/async-raft/latest/async_raft/) for more in-depth details.
This crate differs from other Raft implementations in that:
- It is fully reactive and embraces the async ecosystem. It is driven by actual Raft events taking place in the system as opposed to being driven by a `tick` operation. Batching of messages during replication is still used whenever possible for maximum throughput.
- Storage and network integration is well defined via two traits `RaftStorage` & `RaftNetwork`. This provides applications maximum flexibility in being able to choose their storage and networking mediums. See the [storage](https://async-raft.github.io/async-raft/storage.html) & [network](https://async-raft.github.io/async-raft/network.html) chapters of the guide for more details.
- All interaction with the Raft node is well defined via a single public `Raft` type, which is used to spawn the Raft async task, and to interact with that task. The API for this system is clear and concise. See the [raft](https://async-raft.github.io/async-raft/raft.html) chapter in the guide.
- Log replication is fully pipelined and batched for optimal performance. Log replication also uses a congestion control mechanism to help keep nodes up-to-date as efficiently as possible.
- It fully supports dynamic cluster membership changes according to the Raft spec. See the [`dynamic membership`](https://async-raft.github.io/async-raft/dynamic-membership.html) chapter in the guide. With full support for leader stepdown, and non-voter syncing.
- Details on initial cluster formation, and how to effectively do so from an application's perspective, are discussed in the [cluster formation](https://async-raft.github.io/async-raft/cluster-formation.html) chapter in the guide.
- Automatic log compaction with snapshots, as well as snapshot streaming from the leader node to follower nodes is fully supported and configurable.
- The entire code base is [instrumented with tracing](https://docs.rs/tracing/). This can be used for [standard logging](https://docs.rs/tracing/latest/tracing/index.html#log-compatibility), or for [distributed tracing](https://docs.rs/tracing/latest/tracing/index.html#related-crates), and the verbosity can be [statically configured at compile time](https://docs.rs/tracing/latest/tracing/level_filters/index.html) to completely remove all instrumentation below the configured level.
This implementation strictly adheres to the [Raft spec](https://raft.github.io/raft.pdf) (*pdf warning*), and all data models use the same nomenclature found in the spec for better understandability. This implementation of Raft has integration tests covering all aspects of a Raft cluster's lifecycle including: cluster formation, dynamic membership changes, snapshotting, writing data to a live cluster and more.
If you are building an application using this Raft implementation, open an issue and let me know! I would love to add your project's name & logo to a users list in this project.
### contributing
Check out the [CONTRIBUTING.md](https://github.com/async-raft/async-raft/blob/master/CONTRIBUTING.md) guide for more details on getting started with contributing to this project.
### license
async-raft is licensed under the terms of the MIT License or the Apache License 2.0, at your choosing.
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**NOTE:** the appearance of the "section" symbols `§` throughout this project are references to specific sections of the Raft spec.