integrations redis caching

Redis Cache Integration

Basho’s Redis cache integration with Riak® KV improves application performance by reducing latency and includes built-in cluster management, high availability, automatic data sharding, and the ability to replicate and sync data between Riak KV and Redis.

Write it like Riak. Cache it like Redis.

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The combined power of Riak with Redis caching reduces latency to improve application performance. Riak adds high availability, fault tolerance, and extends operational simplicity to Redis. The Riak cache proxy provides pre-sharding and connection aggregation as a service, which reduces latency and increases addressable cache memory space with lower cost hardware. The Riak cache proxy increases performance by pipelining requests to Redis. While pipelining can be performed at the client, the cache proxy service is ideal for connection aggregation. Pipelining reduces network roundtrips and lowers CPU usage on Redis.

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REDIS FEATURES

High Availability

Raise the roof on availability.
Using the Basho Redis Proxy, the high performance caching capabilities of Redis become highly available, too.

Fast Cache

Because milliseconds matter.
Combining the speed of Redis with the power of Riak KV provides low-latency, high performance at scale.

Automatic Sharding

Just say “no” to manual sharding.
Labor-intensive, error-prone manual sharding is a thing of the past with automatic data sharding across multiple cache servers.

Automatic Data Synchronization

Put critical data in its place.
Data is automatically synchronized between Redis and Riak KV, and the Basho Redis Proxy resolves cache misses without requiring custom code to populate the cache.

Automated Deployment

It’s your time, so do something else.
Easily deploy and configure Redis instances with Riak KV, and auto-start failed instances or disable on failure to reduce manual processes.

Application Simplicity

Keep it simple systematically.
Integrate and update Redis caching, real-time analytics and search technologies to simplify your Big Data Application.