Hazelcast vs Redis

Compare features, pricing, and capabilities to find which solution is best for your needs.

Hazelcast icon

Hazelcast

Hazelcast is a leading open-source distributed in-memory data grid and stream processing platform designed for high-performance, low-latency applications. It provides incredibly fast data access and processing by keeping data in RAM across a cluster of machines, enabling real-time responsiveness. by Hazelcast, Inc.

Open Source
Platforms: Mac OS X Windows Linux
VS
Redis icon

Redis

Redis is an open-source, in-memory data structure store used as a database, cache, and message broker. It supports various data structures like strings, hashes, lists, sets, sorted sets, and more, offering high performance and versatility for modern application development. by Salvatore Sanfilippo

Open Source
Platforms: Mac OS X Windows Linux BSD Self-Hosted
Screenshots:

Comparison Summary

Hazelcast and Redis are both powerful solutions in their space. Hazelcast offers hazelcast is a leading open-source distributed in-memory data grid and stream processing platform designed for high-performance, low-latency applications. it provides incredibly fast data access and processing by keeping data in ram across a cluster of machines, enabling real-time responsiveness., while Redis provides redis is an open-source, in-memory data structure store used as a database, cache, and message broker. it supports various data structures like strings, hashes, lists, sets, sorted sets, and more, offering high performance and versatility for modern application development.. Compare their features and pricing to find the best match for your needs.

Pros & Cons Comparison

Hazelcast

Hazelcast

Analysis & Comparison

Advantages

Extremely low latency due to in-memory data storage.
Highly scalable and fault-tolerant architecture automatically handles data distribution and replication.
Integrated stream processing engine for real-time analytics and event processing.
Offers familiar distributed data structures simplifying development.
Pure Java implementation integrates well with Java ecosystems.
Flexible deployment options including cloud and containers.

Limitations

In-memory nature means data size is limited by available RAM.
Requires operational knowledge to effectively manage and tune large clusters.
Steeper learning curve initially compared to simpler caching solutions.
Persistence requires additional configuration and can introduce complexity.
Redis

Redis

Analysis & Comparison

Advantages

Exceptional speed and low latency due to in-memory storage.
Supports a wide range of versatile data structures.
Robust persistence options for data durability.
Scalable with built-in clustering support.
Can function as an efficient message broker.
Strong community support and extensive documentation.

Limitations

Can be memory-intensive for very large datasets.
Not designed for complex relational queries or joins.
Data must fit largely within available RAM for optimal performance.
Security requires careful configuration and network isolation.

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