Apache Cassandra vs Redis

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

Apache Cassandra icon

Apache Cassandra

Apache Cassandra is a highly scalable, distributed NoSQL database designed to handle large amounts of data across many commodity servers, providing high availability without a single point of failure.

Open Source
Platforms: Mac OS X Windows Linux BSD
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

Apache Cassandra and Redis are both powerful solutions in their space. Apache Cassandra offers apache cassandra is a highly scalable, distributed nosql database designed to handle large amounts of data across many commodity servers, providing high availability without a single point of failure., 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

Apache Cassandra

Apache Cassandra

Analysis & Comparison

Advantages

High availability with no single point of failure.
Excellent linear scalability to handle increasing data volumes.
Fault-tolerant and resilient to node failures.
Designed for high write throughput and low-latency reads.
Tunable consistency allows balancing performance and consistency.

Limitations

Data modeling requires a different approach compared to RDBMS.
Complex transactions like multi-keyspace ACID are not supported.
Operational overhead can be high for large clusters.
CQL is not a full SQL implementation; complex queries may be challenging.
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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