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Learn MorePros of Hazelcast
Pros of RabbitMQ
Pros of Redis
Pros of Hazelcast
- High Availibility11
- Distributed Locking6
- Distributed compute6
- Sharding5
- Load balancing4
- Map-reduce functionality3
- Simple-to-use3
- Written in java. runs on jvm3
- Publish-subscribe3
- Sql query support in cluster wide3
- Optimis locking for map2
- Performance2
- Multiple client language support2
- Rest interface2
- Admin Interface (Management Center)1
- Better Documentation1
- Easy to use1
- Super Fast1
Pros of RabbitMQ
- It's fast and it works with good metrics/monitoring235
- Ease of configuration80
- I like the admin interface60
- Easy to set-up and start with52
- Durable22
- Standard protocols19
- Intuitive work through python19
- Written primarily in Erlang11
- Simply superb9
- Completeness of messaging patterns7
- Reliable4
- Scales to 1 million messages per second4
- Better than most traditional queue based message broker3
- Distributed3
- Supports MQTT3
- Supports AMQP3
- Clear documentation with different scripting language2
- Better routing system2
- Inubit Integration2
- Great ui2
- High performance2
- Reliability2
- Open-source2
- Runs on Open Telecom Platform2
- Clusterable2
- Delayed messages2
- Supports Streams1
- Supports STOMP1
- Supports JMS1
Pros of Redis
- Performance887
- Super fast542
- Ease of use514
- In-memory cache444
- Advanced key-value cache324
- Open source194
- Easy to deploy182
- Stable165
- Free156
- Fast121
- High-Performance42
- High Availability40
- Data Structures35
- Very Scalable32
- Replication24
- Pub/Sub23
- Great community22
- "NoSQL" key-value data store19
- Hashes16
- Sets13
- Sorted Sets11
- Lists10
- NoSQL10
- Async replication9
- BSD licensed9
- Integrates super easy with Sidekiq for Rails background8
- Bitmaps8
- Open Source7
- Keys with a limited time-to-live7
- Lua scripting6
- Strings6
- Awesomeness for Free5
- Hyperloglogs5
- Runs server side LUA4
- Transactions4
- Networked4
- Outstanding performance4
- Feature Rich4
- Written in ANSI C4
- LRU eviction of keys4
- Data structure server3
- Performance & ease of use3
- Temporarily kept on disk2
- Dont save data if no subscribers are found2
- Automatic failover2
- Easy to use2
- Scalable2
- Channels concept2
- Object [key/value] size each 500 MB2
- Existing Laravel Integration2
- Simple2
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Cons of Hazelcast
Cons of RabbitMQ
Cons of Redis
Cons of Hazelcast
- License needed for SSL4
Cons of RabbitMQ
- Too complicated cluster/HA config and management9
- Needs Erlang runtime. Need ops good with Erlang runtime6
- Configuration must be done first, not by your code5
- Slow4
Cons of Redis
- Cannot query objects directly15
- No secondary indexes for non-numeric data types3
- No WAL1
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What is Hazelcast?
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.
What is RabbitMQ?
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
What is Redis?
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
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Jobs that mention Hazelcast, RabbitMQ, and Redis as a desired skillset
What companies use Hazelcast?
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What companies use Hazelcast?
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What tools integrate with Hazelcast?
What tools integrate with RabbitMQ?
What tools integrate with Redis?
What tools integrate with Hazelcast?
What tools integrate with RabbitMQ?
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What are some alternatives to Hazelcast, RabbitMQ, and Redis?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
Memcached
Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
Apache Ignite
It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale
Kafka
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.