cachegrand
glommio
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| cachegrand | glommio | |
|---|---|---|
| 24 | 29 | |
| 963 | 2,835 | |
| - | 2.3% | |
| 8.0 | 6.8 | |
| 6 months ago | 5 days ago | |
| C | Rust | |
| BSD 3-clause "New" or "Revised" License | 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.
cachegrand
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C++ caching library with tiering (RAM + disc)
Closest that comes to my mind is CacheGrand. It doesn’t have some of the features yet, but I believe @daniele_dll is working on it!
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[PC][Switzerland] Cheap Rackspace
I use this HW for benchmarking and testing my open source project cachegrand ( https://github.com/danielealbano/cachegrand)
- cachegrand
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Cachegrand, a fast, Redis compatible, KV store – hashtable documentation
https://github.com/danielealbano/cachegrand/blob/main/docs/a...
When tested with memtier_benchmark, using the Redis protocol, cachegrand itself, on the benchmarking hardware, thanks to the implemented hashtable can reach up to 5 million GET op/s and up to 4.5 million UPSERT op/s without batching, with it up to 60 million GET op/s and up to 26 million UPSERT op/s!
- cachegrand - a blazing fast, Redis compatible, Key-Value store builf for today's hardware - hashtable documentation - capable of delivering up to 112 GET mop/s and 85 UPSERT mop/s on a EPYC 7502P
- Show HN: Cachegrand – a fast OSS Key-Value store built for modern hardware
- Cachegrand – a modern OSS Key-Value store built for today's hardware
glommio
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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.
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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.
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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...
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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.
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Why does Actix-web's handler not require Send?
I assume Tokio itself, see e.g monoio or glommio, but also Seastar for C++.
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How does async Rust work
https://github.com/DataDog/glommio Rust thread per core library.
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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
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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.
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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:
https://github.com/bytedance/monoio
https://github.com/DataDog/glommio/issues/554
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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:
https://github.com/DataDog/glommio
What are some alternatives?
dragonfly - A modern replacement for Redis and Memcached
tokio - A runtime for writing reliable asynchronous applications with Rust. Provides I/O, networking, scheduling, timers, ...
varnish-cache - Varnish Cache source code repository
tokio-uring - An io_uring backed runtime for Rust
examples - Example data structures and algorithms
Seastar - High performance server-side application framework
midi-redis - A toy memory store with great performance
monoio - Rust async runtime based on io-uring.
async-std - Async version of the Rust standard library
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.