Redis e Memcached - Daniel Naves - Omnilogic
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Redis and Memcached are both open-source, in-memory key-value data structures stores that are commonly used for caching, but Redis has additional features like persistence, data structures, and pub/sub capabilities that make it more flexible than the simpler Memcached. Real-world use cases for Redis include caching page fragments to speed up websites by 5x, job queuing with persistence and multi-queue/worker support, and caching model predictions to speed up machine learning workflows by 100x.
Redis e Memcached - Daniel Naves - Omnilogic
- 1. Redis vs Memcached Daniel Naves de Carvalho - [email protected]
- 2. OmniLogic • Since nov/2009 • Data-Mining • Computational Intelligence • Optimization • Business Intelligence
- 3. Memcached • Free & open source • High-performance • Distributed memory object caching system • Generic in nature, but intended for use in speeding up dynamic web applications by alleviating database load. • In-memory key-value store for small chunks of arbitrary data (strings, objects from database calls, API calls etc) • At heart it is a simple Key-Value store
- 4. Memcached - Clients • C / C++ • PHP • Java • Python • Ruby • Perl • Windows/.NET • MySQL • PostgreSQL • Erlang • Lua • Lisp • ColdFusion • OCaml • Io • etc
- 5. Features • Simple Key-Value Store • Servers are disconected from each other • Forgetting data is a feature(LRU) • O(1)
- 6. Redis vs Memcached Redis Memcached In Memory x x Persistent x Atomic x x Consistent x x Replication x Authentication x Key / Value x x Key Enumeration x Key / Value buckets x
- 7. Redis vs Memcached Redis Memcached Maximum Key Length 2^31bytes 250 bytes Maximum String size 512m 1m Data Structures x Channel Pub/Sub x Consistent hasing x x Memory Usage 10-20% less Speed(Single Instance, Multicore) 100.000 req/s 125.000 req/s Speed(Multiple Instances, Single Thread) 200.000 req/s 200.000 req/s
- 8. Redis – Real Use Cases • R eal-time model-prediction caching • Page fragments caching • Jobs Queue
- 9. Redis – Network layout
- 10. Page fragments caching • Speedup +5x • Low memory usage • Faster than pre-render file caching
- 11. Jobs Queue • Easy to maintain • Persistent • Multi-queue multi-workers
- 12. Resque
- 13. R eal-time model-prediction caching • Speed-up +100x • Faster sorting vs Lib Sorting • Easy to maintain • Scales horizontally
- 14. Questions???