prolly-trees
Hash consistent search trees. (by mikeal)
bft-json-crdt
🏰 the first JSON-like Byzantine Fault Tolerant CRDT (by jackyzha0)
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prolly-trees | bft-json-crdt | |
---|---|---|
1 | 2 | |
86 | 188 | |
- | - | |
3.4 | 10.0 | |
10 months ago | over 1 year ago | |
JavaScript | Rust | |
- | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
prolly-trees
Posts with mentions or reviews of prolly-trees.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-21.
-
Building a BFT JSON CRDT
Check out this implementation of hash-stable trees. The same dataset generates the same Merkle hash, regardless of insertion orders. This makes verifiable sync computationally efficient. https://github.com/mikeal/prolly-trees
bft-json-crdt
Posts with mentions or reviews of bft-json-crdt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-21.
-
Building a BFT JSON CRDT
I'm quite surprised by the [benchmarks versus Automerge JS & Rust](https://github.com/jackyzha0/bft-json-crdt#benchmarks) when it comes to memory:
> Ours (Basic) 27.6MB
> Ours (BFT) 59.5MB
> Automerge (Rust) 232.5MB
I would expect adding the public key tracking to use more memory; I wonder how Automerge is spending so much more memory. Possibly on a bunch of internal caches or memoization that give the order-of-magnitude improvement in speed?
> Ops: 100k
> Ours (Basic) 9.321s
> Ours (BFT) 38.842s
> Automerge (Rust) 0.597s
What are some alternatives?
When comparing prolly-trees and bft-json-crdt you can also consider the following projects:
y-sweet - A standalone yjs server with persistence to S3 or filesystem.
diamond-types - The world's fastest CRDT. WIP.
overlord - Overlord consensus protocol.
cr-sqlite - Convergent, Replicated SQLite. Multi-writer and CRDT support for SQLite
AlephBFT - Rust implementation of Aleph consensus protocol