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Hazelcast vs Redis: What are the differences?
Hazelcast: Clustering and highly scalable data distribution platform for Java. With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution; Redis: An in-memory database that persists on disk. Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
Hazelcast and Redis belong to "In-Memory Databases" category of the tech stack.
"High Availibility" is the primary reason why developers consider Hazelcast over the competitors, whereas "Performance" was stated as the key factor in picking Redis.
Hazelcast and Redis are both open source tools. Redis with 37.1K GitHub stars and 14.3K forks on GitHub appears to be more popular than Hazelcast with 3.15K GitHub stars and 1.15K GitHub forks.
reddit, Instacart, and Slack are some of the popular companies that use Redis, whereas Hazelcast is used by Yammer, Seat Pagine Gialle, and Stormpath. Redis has a broader approval, being mentioned in 3239 company stacks & 1732 developers stacks; compared to Hazelcast, which is listed in 25 company stacks and 15 developer stacks.
Pros of Hazelcast
- High Availibility9
- Distributed Locking6
- Distributed compute5
- Sharding5
- Load balancing4
- Map-reduce functionality3
- Publish-subscribe3
- Sql query support in cluster wide3
- Written in java. runs on jvm2
- Simple-to-use2
- Multiple client language support2
- Rest interface2
- Optimis locking for map2
- Easy to use1
- Performance1
- Super Fast1
- Admin Interface (Management Center)1
- Better Documentation1
Pros of Redis
- Performance877
- Super fast535
- Ease of use511
- In-memory cache442
- Advanced key-value cache321
- Open source190
- Easy to deploy179
- Stable163
- Free153
- Fast120
- High-Performance40
- High Availability39
- Data Structures34
- Very Scalable32
- Replication23
- Great community20
- Pub/Sub19
- "NoSQL" key-value data store17
- Hashes14
- Sets12
- Sorted Sets10
- Lists9
- BSD licensed8
- NoSQL8
- Async replication7
- Integrates super easy with Sidekiq for Rails background7
- Bitmaps7
- Open Source6
- Keys with a limited time-to-live6
- Strings5
- Lua scripting5
- Awesomeness for Free!4
- Hyperloglogs4
- outstanding performance3
- Runs server side LUA3
- Networked3
- LRU eviction of keys3
- Written in ANSI C3
- Feature Rich3
- Transactions3
- Data structure server2
- Performance & ease of use2
- Existing Laravel Integration1
- Automatic failover1
- Easy to use1
- Object [key/value] size each 500 MB1
- Simple1
- Channels concept1
- Scalable1
- Temporarily kept on disk1
- Dont save data if no subscribers are found1
- Jk0
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Cons of Hazelcast
- License needed for SSL3
Cons of Redis
- Cannot query objects directly12
- No WAL1
- No secondary indexes for non-numeric data types1
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What is Hazelcast?
What is Redis?
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What companies use Hazelcast?
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What tools integrate with Hazelcast?
What tools integrate with Redis?
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Blog Posts
Redis is a good caching tool for a cluster, but our application had performance issues while using Aws Elasticache Redis since some page had 3000 cache hits per a page load and Redis just couldn't quickly process them all in once + latency and object deseialization time - page load took 8-9 seconds. We create a custom hybrid caching based on Redis and EhCache which worked great for our goals. Check it out on github, it's called HybriCache - https://github.com/batir-akhmerov/hybricache.
Redis is used for storing all ephemeral (that's data you don't necessarily want to store permanently) user data, such as mapping of session IDs (stored in cookies) to current session variables at Cloudcraft.co. The many datastructures supported by Redis also makes it an excellent caching and realtime statistics layer. It doesn't hurt that the author, Antirez, is the nicest guy ever! These days, I would be really hard pressed to find any situation where I would pick something like Memcached over Redis.
Trello uses Redis for ephemeral data that needs to be shared between server processes but not persisted to disk. Things like the activity level of a session or a temporary OpenID key are stored in Redis, and the application is built to recover gracefully if any of these (or all of them) are lost. We run with allkeys-lru enabled and about five times as much space as its actual working set needs, so Redis automatically discards data that hasn’t been accessed lately, and reconstructs it when necessary.
The UI has message inbox that is sent a message when you get a new badge, receive a message, significant event, etc. Done using WebSockets and is powered by redis. Redis has 2 slaves, SQL has 2 replicas, tag engine has 3 nodes, elastic has 3 nodes - any other service has high availability as well (and exists in both data centers).
Redis makes certain operations very easy. When I need a high-availability store, I typically look elsewhere, but for rapid development with the ability to land on your feet in prod, Redis is great. The available data types make it easy to build non-trivial indexes that would require complex queries in postgres.
I use Redis for cacheing, data storage, mining and augmentation, proprietary distributed event system for disparate apps and services to talk to each other, and more. Redis has some very useful native data types for tracking, slicing and dicing information.