Redis vs Hazelcast : Which is Better?

Redis icon

Redis

Redis is an in-memory database open-source software. Developed by Salvatore Sanfilippo

License: Open Source

Categories: Development

Apps available for Mac OS X Windows Linux BSD Self-Hosted

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Hazelcast icon

Hazelcast

Hazelcast is an open source in-memory data grid based on Java. Developed by Hazelcast, Inc.

License: Open Source

Categories: Development

Apps available for Mac OS X Windows Linux

Redis VS Hazelcast

Redis is primarily a high-performance key-value store with rich data structure support, making it ideal for caching and real-time analytics. In contrast, Hazelcast is a distributed in-memory data grid that excels in scalability and complex data processing, making it suitable for large applications requiring real-time data handling.

Redis

Pros:

  • High performance for key-value operations
  • Rich data structure support
  • Built-in replication and persistence
  • Strong community support
  • Supports various programming languages
  • Advanced features like Pub/Sub and Streams
  • Data expiry and eviction policies
  • Easy to deploy and manage
  • Well-suited for caching scenarios
  • Supports transactions for atomic operations

Cons:

  • Limited to key-value store and no distributed data grid
  • Less suitable for large-scale distributed systems
  • Persistence can lead to performance overhead
  • Limited querying capabilities compared to SQL
  • Data loss risk in certain failure scenarios

Hazelcast

Pros:

  • Distributed in-memory data grid
  • Strong scalability and horizontal scaling
  • Built-in partitioning and replication
  • Supports multiple data structures
  • Integrated with big data and cloud solutions
  • Rich set of distributed computing features
  • Automatic data rebalancing
  • Supports querying with SQL-like syntax
  • Good for real-time analytics
  • Java-based with various client support

Cons:

  • More complex to set up and manage
  • Java-centric, which may limit language flexibility
  • Higher resource consumption due to in-memory grid
  • Some advanced features may have a steep learning curve
  • Not as widely adopted as Redis

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