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


+ 1

+ 1
Add tool

Hazelcast vs Memcached: What are the differences?


In this article, we will compare the key differences between Hazelcast and Memcached, two popular distributed caching solutions.

  1. Data Model: Hazelcast is an in-memory data grid that allows storing and querying data using a distributed and scalable data model. It supports a wide range of data structures such as maps, queues, topics, and locks. On the other hand, Memcached is a key-value store that stores data in a simple key-value format without any additional data structures or query capabilities.

  2. Data Persistence: Hazelcast provides native support for data persistence, allowing the caching of large datasets and high availability by persisting the data to disk. This ensures that data is not lost in case of a system failure or restart. In contrast, Memcached does not offer built-in data persistence. All the data is stored in memory and will be lost if the system crashes or restarts.

  3. Distributed Computing: Hazelcast offers a wide range of distributed computing capabilities such as distributed processing, distributed task execution, and distributed computing paradigms like MapReduce. It allows developers to perform parallel computation on large datasets across a cluster of servers. Memcached, on the other hand, focuses solely on caching data and does not provide any distributed computing capabilities.

  4. Client Libraries: Hazelcast provides client libraries for various programming languages, making it easy for developers to integrate Hazelcast into their applications. These client libraries provide a simple API to interact with the Hazelcast cluster. Memcached also offers client libraries for multiple programming languages, enabling seamless integration with applications.

  5. Consistency Guarantees: Hazelcast provides strong consistency guarantees for data stored in the cluster. It ensures that data is always up to date and consistent across the cluster by using distributed locking and synchronization mechanisms. Memcached, on the other hand, does not provide any built-in consistency guarantees. It is eventually consistent and may not provide the latest data immediately after an update.

  6. Cluster Management: Hazelcast includes advanced cluster management features, such as automatic discovery of cluster members, automatic failover and recovery, and dynamic scaling of the cluster. It provides tools and APIs for monitoring and managing the cluster effectively. Memcached, on the other hand, is more lightweight and does not provide extensive cluster management features. Cluster management needs to be implemented separately.

In Summary, Hazelcast is an in-memory data grid with advanced distributed computing capabilities, support for data persistence, strong consistency guarantees, and comprehensive cluster management features. Memcached, on the other hand, is a simpler key-value store focused on caching data without built-in data persistence, distributed computing, or extensive cluster management capabilities.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
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

Sign up to add or upvote prosMake informed product decisions

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

Sign up to add or upvote consMake informed product decisions

What companies use Hazelcast?
What companies use Memcached?
See which teams inside your own company are using Hazelcast or Memcached.
Sign up for StackShare EnterpriseLearn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with Hazelcast?
What tools integrate with Memcached?

Sign up to get full access to all the tool integrationsMake informed product decisions

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