theine-go
coherence-go-client
| theine-go | coherence-go-client | |
|---|---|---|
| 5 | - | |
| 220 | 8 | |
| - | - | |
| 6.9 | 7.8 | |
| 3 months ago | 13 days ago | |
| Go | Go | |
| MIT License | Universal Permissive License v1.0 |
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.
theine-go
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Otter, Fastest Go in-memory cache based on S3-FIFO algorithm
In fact, lock-free queues have several problems at once, which prompted me to give up on them almost immediately.
1. Yes, S3-FIFO can be implemented using lock-free queues, but the problem is that each write to a filled cache using this design will cause a large number of additional atomic operations not friendly to the processor's cache, while bp-wrapper on the contrary amortizes this load. And reading with frequency update on hot entries can have a bad effect on performance. In many ways this is exactly what the last posts in my discussion with Ben are about (not really about this, but the current problem with otter read speed is caused by a similar problem). https://github.com/Yiling-J/theine-go/issues/29#issuecomment...
2. But the main problem for me is not even that. Lock-free queues work fine as long as you only need to support Get and Set operations, but as soon as you want to add features to your cache, the complexity of the implementation starts to increase, and some features are very hard to add to such a structure. Also, improving the eviction policy is under a big question mark, because not only do you have to think about how to improve the eviction policy, but also how to avoid locks while doing so or how not to slow down the implementation with your improvements. BP-Wrapper has no such problems at all, allows you to use any eviction policy and focus on improving different parts of your cache independently of each other.
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rueidis v1, a redis client with client-side caching, has been released under redis org
CacheStore is an interface so I can use a different local cache instead? For example my adaptive cache package Theine, I think the hit ratio will be much higer than the default LRU one.
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Theine 0.2.0 released. A generic cache which has adaptive hit ratio optimization and proactive ttl expiration
0.2.0 add removal callback and loading cache(with thundering herd protection), take a look: https://github.com/Yiling-J/theine-go
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Theine - High performance in-memory cache
Theine: https://github.com/Yiling-J/theine-go
coherence-go-client
We haven't tracked posts mentioning coherence-go-client yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
imcache - A zero-dependency generic in-memory cache Go library
nscache - A Go caching framework that supports multiple data source drivers
hazelcast-go-client - Hazelcast Go Client
rueidis - A fast Golang Redis client that supports Client Side Caching, Auto Pipelining, Generics OM, RedisJSON, RedisBloom, RediSearch, etc.
coherence - Oracle Coherence Community Edition
BigCache - Efficient cache for gigabytes of data written in Go.
grpc_microservices - This project is a POC of the API Composition Pattern but using gRPC, the idea is having the same proto file implemented in different services (micro or nano) and each service returns a piece of the information to the gateway.
ristretto - A high performance memory-bound Go cache
otter - A high performance lockless cache for Go.
ptg - 💥Performance testing tool (Go), It is also a GUI gRPC client.