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Redis vs. Aerospike

Beyond the cache

Start with a better cache, and gain an ultra-fast, infinite-scale database that powers your next breakthrough.

Some of the Redis customers that made the switch

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Competitive research

Redis vs. Aerospike

As workloads grow, Redis users often face rising costs, scalability issues, and operational complexity. Aerospike offers a more efficient, scalable, low-latency alternative for high-demand applications.

5 reasons to consider Aerospike over Redis

Discover five powerful ways Aerospike outperforms Redis, delivering unmatched efficiency, performance, and scalability for your most demanding workloads.

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Effortless scaling

Aerospike scales seamlessly with its multi-threaded, multi-core clustered system.

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Ultra-fast performance

Optimized for predictable low latency, Aerospike delivers consistent speed, even at petabyte scale.

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Lowest TCO

Cut infrastructure costs and memory needs while maintaining top performance under heavy demand.

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Reduce sprawl

Aerospike’s high-density nodes and unified storage manage data efficiently across memory and SSDs.

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Smallest carbon footprint

Use 80% fewer servers for lower costs, reduced environmental impact, and greater sustainability.

More than a cache, a complete solution

Aerospike goes beyond caching to deliver an ultra-fast, infinitely scalable database for real-time, mission-critical applications. Built to handle multi-terabyte workloads with ultra-low latency and unmatched cost efficiency, Aerospike seamlessly powers caching and so much more—empowering you to scale, adapt, and innovate without limits.

Aerospike vs. Redis comparison

See key differences between the two solutions at a glance.

 


Redis Aerospike
Scalability Not distributed - Clustering is an add-on that adds overhead and complexity. Built for scale-out - Automatic sharding with no manual data redistribution.
Performance at scale Single-threaded limits scale - Can’t fully utilize multi-core processors, requiring many instances. Multi-threaded, maximizes CPUs - Efficient scale-up with fewer nodes.
Data persistence Risk of data loss - Snapshots and append-only files (AOFs) don’t guarantee zero data loss. Strong consistency, durable storage - Built-in persistence ensures data integrity.
Cost efficiency High RAM dependency - Expensive infrastructure due to in-memory-only design. Hybrid storage, lower costs - Supports SSDs while maintaining high performance.
Operational overhead Manual sharding required - Complex cluster coordination with external proxies. Auto-sharding, lower admin effort - Self-healing and rebalancing built-in.
Data model Basic key-value only - No native support for JSON, graphs, or vector search. Multi-model: JSON, vectors, graphs - Supports advanced data types natively.

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