dragonfly
glommio
Our great sponsors
dragonfly | glommio | |
---|---|---|
49 | 29 | |
23,696 | 2,828 | |
5.8% | 2.1% | |
9.9 | 6.8 | |
3 days ago | 6 days ago | |
C++ | Rust | |
BSL 1.1 | GNU General Public License v3.0 or later |
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.
dragonfly
-
Redict is an independent, copyleft fork of Redis
https://github.com/dragonflydb/dragonfly is another option. Not a fork but API-compatible reimplementation.
- Redis License Changed
-
Scaling Real-Time Leaderboards with Dragonfly
Our journey will involve leveraging the capabilities of Dragonfly, a highly efficient drop-in replacement for Redis, known for its ultra-high throughput and multi-threaded share-nothing architecture. Specifically, we'll be utilizing two of Dragonfly's data types: Sorted-Set and Hash. These data structures are perfect for handling real-time data and ranking systems, making them ideal for our leaderboards.
-
Announcing Dragonfly Search
2023 has been a year with remarkable advancements in AI capabilities, and at Dragonfly, we are thrilled to power new use cases with our latest release: Dragonfly Search. This new feature set, debuting in Dragonfly v1.13, is a subset of RediSearch-compatible commands implemented natively in Dragonfly, allowing for both vector search and faceted search use cases in the highly scalable and performant Dragonfly in-memory data store.
- Dragonfly v1.10.0
-
Dragonfly Cache Design
If you have not heard about Dragonfly - please check it out. It uses - what I hope - novel and interesting ideas backed up by the research from recent years [1] and [2]. It's meant to fix many problems that exist with Redis today. I have been working on Dragonfly for the last 7 months and it has been one of the more interesting and challenging projects I've ever done!
-
Generating Income from Open Source
I recently ran across the the license for Dragonfly [1] which has some restrictions (rights reserved), but 5 years after the license date the license switches to Apache 2.0. Basically a timed-limited rights reservation. I don't hate it. I might even contribute to such a project for free.
I would consider something like this: When I release code, it's rights reserved for 5 years, then open-source (and this baked into an irrevocable license). Anyone may use the software for non-commercial purposes. Anyone may contribute, those who contribute will be granted permission for commercial use if I deem their contributions significant enough. Anyone may distribute the software under these terms.
If such a model became popular, I have a hard time imagining it could make things any worse. It might even accelerate open-source development. You might say, "but it's not open-source", fair enough, but we can view it as open-source contribution with a delay. For example, if this model became wildely popular this year, and we saw great progress with this model, then come 2028 we would be flooded with new open-source software and ultimately might be better off than it would have been without this model.
(And this whole thing makes me rethink copyright and patents and how much they really contribute to society. Perhaps they should be shortened?)
[1]: https://github.com/dragonflydb/dragonfly/blob/main/LICENSE.m...
- dragonflydb/dragonfly: A modern replacement for Redis and Memcached
-
Redis HA on k8s without Sentinel?
Maybe check out https://www.dragonflydb.io/ It claims to have a full redis implementation.
- Dragonfly is about 10x slower than Redis
glommio
-
I want to share my latest hobby project, dbeel: A distributed thread-per-core nosql db written in rust
I used glommio as the async executor (instead of something like tokio), and it is wonderful. For people wondering whether it's "good enough" or to use C++ and seastar (as I have thought about a lot before starting this project), take the leap of faith, it's fast - both in terms of run time and to code.
-
The State of Async Rust
My understanding is you always need a runtime, somethings needs to drive the async flow. But there are others on the market, just not without the.. market domination... of tokio.
https://github.com/smol-rs/smol looks promising simply for being minimal
https://github.com/bytedance/monoio looks potentially easier to work with than tokio
https://github.com/DataDog/glommio is built around linux io_uring and seems somewhat promising for performance reasons.
I haven't played with any of these yet, because Tokio is unfortunately the path of least resistance. And a bit viral in how it's infected tings.
-
Learning Async Rust with Too Many Web Servers
I think you missed one which is based on io_uring [1].
In my benchmarks with a slightly tweaked version it was 2x faster than Nginx and and 30x faster than Python's SimpleHttpServer.
[1] https://github.com/DataDog/glommio/blob/master/examples/hype...
-
How much reason is there to be multi-threaded in the k8s environment
b) It's proven now e.g Seastar, Glommio that the fastest way to run a multi-threaded application is to have one instance with one thread pinned per CPU core. Then to have fibers/lightweight threads on top handling all of the asynchronous code. Your approach of lots of instances is the slowest so there will be a ton of unnecessary thread context-switching.
-
Why does Actix-web's handler not require Send?
I assume Tokio itself, see e.g monoio or glommio, but also Seastar for C++.
-
How does async Rust work
https://github.com/DataDog/glommio Rust thread per core library.
-
Use io_uring for network I/O
> Few of us have really figured out io_uring. But that doesn't mean it is slower.
seastar.io is a high level framework that I believe has "figured out" io_uring, with additional caveats the framework imposes (which is honestly freeing).
Additionally the rust equivalent: https://github.com/DataDog/glommio
-
Is async runtime (Tokio) overhead significant for a "real-time" video stream server?
This use case is perfect for https://github.com/DataDog/glommio which is a thread-per-core runtime that is appropriate for latency sensitive code.
-
Blessed.rs – An unofficial guide to the Rust ecosystem
It's worth mentioning: Under "Async Executors", for "io_uring" there is only "Glommio"
I recently found out that ByteDance has a competitor library which supposedly has better performance:
-
Building a High-Performance DB Buffer Pool in Zig W\ Io_uring New Fixed-Buffers
FYI, Datadog has a Rust library for scheduling things to run thread-per-core with io_uring
It'd be really useful for DB use cases:
What are some alternatives?
KeyDB - A Multithreaded Fork of Redis
tokio - A runtime for writing reliable asynchronous applications with Rust. Provides I/O, networking, scheduling, timers, ...
skytable - Skytable is a modern scalable NoSQL database with BlueQL, designed for performance, scalability and flexibility. Skytable gives you spaces, models, data types, complex collections and more to build powerful experiences
tokio-uring - An io_uring backed runtime for Rust
Redis - Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.
Seastar - High performance server-side application framework
Memcached - memcached development tree
monoio - Rust async runtime based on io-uring.
Aerospike - Aerospike Database Server – flash-optimized, in-memory, nosql database
MIO - Metal I/O library for Rust.
webdis - A Redis HTTP interface with JSON output
actix-web - Actix Web is a powerful, pragmatic, and extremely fast web framework for Rust.