Aerospike Vector opens new approaches to AI-driven recommendationsWebinar registration
In-memory caching

Consolidate expensive legacy cache

Combine isolated caches across your organization using less data and with more precision in your data eviction strategies.

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More precise caching

Precision Least Recently Used (LRU) cache eviction strategy that guarantees the data you need is there when you need it.

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Few servers, less risk

Proven resource efficiency means more efficient caching, lower cost of operations, and a caching service that can rapidly scale up and down.

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More caching, less memory

In-memory caching with in-line compression gives applications access to a larger memory footprint without an added cost.

Benefits

What makes Aerospike the best in-memory cache?

To achieve performance goals, your applications need the speed of a cache with the persistence and resiliency of an always-on database. Used as an in-memory cache, Aerospike delivers sustained high throughput rates in distributed environments with sub-millisecond latency.

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Resource efficiency

Aerospike uses less memory (with in-line compression), less CPU, resulting in smaller clusters and lower TCO.

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Greater durability

Aerospike features production-tested stability, fast automated recovery, auto-scaling, and auto-healing capabilities.

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Proven speed

Aerospike delivers sub-millisecond performance as an in-memory database, with high-speed persistence on flash and hybrid memory configurations.

Use cases

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Content caching

Simple content caching of media or thumbnails reduces requests to storage. By reading frequently accessed data from the cache, performance can be improved without impacting traditional data architecture.

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User session store

User profile and web history data can be used in a shopping cart, personalization in a leaderboard, and real-time recommendation engine.

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Speed up access to backend data stores

Legacy mainframe, data warehouse and relational systems were not designed to operate at cloud scale and can be overwhelmed by the volume of requests as usage grows.