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Hazelcast

Clustering and highly scalable data distribution platform for Java
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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.
Hazelcast is a tool in the In-Memory Databases category of a tech stack.
Hazelcast is an open source tool with 4.2K GitHub stars and 1.4K GitHub forks. Here’s a link to Hazelcast's open source repository on GitHub

Who uses Hazelcast?

Companies
47 companies reportedly use Hazelcast in their tech stacks, including Hepsiburada, Platform, and bigin.

Developers
167 developers on StackShare have stated that they use Hazelcast.

Hazelcast Integrations

Java, Spring, ContainerShip, Jooby, and VRaptor are some of the popular tools that integrate with Hazelcast. Here's a list of all 5 tools that integrate with Hazelcast.
Pros of Hazelcast
9
High Availibility
6
Distributed Locking
5
Sharding
5
Distributed compute
4
Load balancing
3
Map-reduce functionality
3
Sql query support in cluster wide
3
Publish-subscribe
2
Multiple client language support
2
Written in java. runs on jvm
2
Rest interface
2
Optimis locking for map
2
Simple-to-use
1
Admin Interface (Management Center)
1
Super Fast
1
Better Documentation
1
Easy to use
1
Performance

Hazelcast's Features

  • Distributed implementations of java.util.{Queue, Set, List, Map}
  • Distributed implementation of java.util.concurrent.locks.Lock
  • Distributed implementation of java.util.concurrent.ExecutorService
  • Distributed MultiMap for one-to-many relationships
  • Distributed Topic for publish/subscribe messaging
  • Synchronous (write-through) and asynchronous (write-behind) persistence
  • Transaction support
  • Socket level encryption support for secure clusters
  • Second level cache provider for Hibernate
  • Monitoring and management of the cluster via JMX
  • Dynamic HTTP session clustering
  • Support for cluster info and membership events
  • Dynamic discovery, scaling, partitioning with backups and fail-over

Hazelcast Alternatives & Comparisons

What are some alternatives to Hazelcast?
Redis
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.
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
See all alternatives

Hazelcast's Followers
316 developers follow Hazelcast to keep up with related blogs and decisions.