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Apache Ignite

78
133
+ 1
29
Hazelcast

279
404
+ 1
56
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Apache Ignite vs Hazelcast: What are the differences?

Developers describe Apache Ignite as "An open-source distributed database, caching and processing platform *". It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale. On the other hand, *Hazelcast** is detailed as "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.

Apache Ignite and Hazelcast can be categorized as "In-Memory Databases" tools.

Some of the features offered by Apache Ignite are:

  • Memory-Centric Storage
  • Distributed SQL
  • Distributed Key-Value

On the other hand, Hazelcast provides the following key 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

Apache Ignite and Hazelcast are both open source tools. Hazelcast with 3.25K GitHub stars and 1.18K forks on GitHub appears to be more popular than Apache Ignite with 2.67K GitHub stars and 1.3K GitHub forks.

Yammer, Seat Pagine Gialle, and Stormpath are some of the popular companies that use Hazelcast, whereas Apache Ignite is used by LabNetwork, Element Analytics, and Leads Software. Hazelcast has a broader approval, being mentioned in 35 company stacks & 81 developers stacks; compared to Apache Ignite, which is listed in 4 company stacks and 4 developer stacks.

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Pros of Apache Ignite
Pros of Hazelcast
  • 4
    Written in java. runs on jvm
  • 4
    Free
  • 3
    Load balancing
  • 3
    Multiple client language support
  • 3
    Sql query support in cluster wide
  • 3
    Rest interface
  • 3
    High Avaliability
  • 2
    Better Documentation
  • 2
    Easy to use
  • 1
    Distributed compute
  • 1
    Distributed Locking
  • 10
    High Availibility
  • 6
    Distributed Locking
  • 5
    Distributed compute
  • 5
    Sharding
  • 4
    Load balancing
  • 3
    Sql query support in cluster wide
  • 3
    Map-reduce functionality
  • 3
    Written in java. runs on jvm
  • 3
    Publish-subscribe
  • 2
    Performance
  • 2
    Simple-to-use
  • 2
    Multiple client language support
  • 2
    Rest interface
  • 2
    Optimis locking for map
  • 1
    Super Fast
  • 1
    Admin Interface (Management Center)
  • 1
    Better Documentation
  • 1
    Easy to use

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Cons of Apache Ignite
Cons of Hazelcast
    Be the first to leave a con
    • 3
      License needed for SSL

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    No Stats

    What is 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

    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.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use Apache Ignite?
    What companies use Hazelcast?
    See which teams inside your own company are using Apache Ignite or Hazelcast.
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    What tools integrate with Apache Ignite?
    What tools integrate with Hazelcast?

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    What are some alternatives to Apache Ignite and Hazelcast?
    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.
    MySQL
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    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.
    Elasticsearch
    Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
    See all alternatives