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Hazelcast vs Memcached: 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; Memcached: High-performance, distributed memory object caching system. 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.

Hazelcast and Memcached are primarily classified as "In-Memory Databases" and "Databases" tools respectively.

"High Availibility" is the top reason why over 4 developers like Hazelcast, while over 133 developers mention "Fast object cache" as the leading cause for choosing Memcached.

Hazelcast and Memcached are both open source tools. Memcached with 9K GitHub stars and 2.6K forks on GitHub appears to be more popular than Hazelcast with 3.18K GitHub stars and 1.16K GitHub forks.

According to the StackShare community, Memcached has a broader approval, being mentioned in 756 company stacks & 267 developers stacks; compared to Hazelcast, which is listed in 26 company stacks and 16 developer stacks.

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Pros of Hazelcast
Pros of Memcached
  • 11
    High Availibility
  • 6
    Distributed Locking
  • 6
    Distributed compute
  • 5
  • 4
    Load balancing
  • 3
    Map-reduce functionality
  • 3
  • 3
    Written in java. runs on jvm
  • 3
  • 3
    Sql query support in cluster wide
  • 2
    Optimis locking for map
  • 2
  • 2
    Multiple client language support
  • 2
    Rest interface
  • 1
    Admin Interface (Management Center)
  • 1
    Better Documentation
  • 1
    Easy to use
  • 1
    Super Fast
  • 139
    Fast object cache
  • 129
  • 91
  • 65
  • 33
    Distributed caching system
  • 11
    Improved response time and throughput
  • 3
    Great for caching HTML
  • 2

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Cons of Hazelcast
Cons of Memcached
  • 4
    License needed for SSL
  • 2
    Only caches simple types

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

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What are some alternatives to Hazelcast and Memcached?
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.
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.
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.
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
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
See all alternatives