Query caching reduces data latency by providing fast queries against a slower database. That can be valuable in many programming scenarios, but it is especially useful when developers need to speed up repeated SQL queries from a relational database or during a migration to microservices starting with legacy systems.Use Redis Enterprise for query caching to reduce data latency and to power faster, scalable, simplified applications.
Queries from each microservice or application are sent to a Redis Enterprise database acting as a cache.
When the Redis Enterprise database contains the data, it is delivered to the application. The query is used as the key and the serialized result set as the value in a string data structure. And it does this super-fast, with sub-millisecond latency.
If Redis Enterprise doesn’t contain the data, the database processes it and then stores it in Redis Enterprise, so that future requests are retrieved fast.
|The problem||The Redis Enterprise solution|
|Latency encountered with often-repeatable queries|| Redis Enterprise provides a real-time cache and database that offers low-latency caching to speed up repeatable SQL queries.|
|The lack of system-wide standardization across many microservices, which results in high maintenance costs||Redis Smart Cache improves development velocity and reduces costs as a transparent no-code solution for query caching with Redis Enterprise. It also provide insights about JDBC workloads, so developers can make smart decisions on which queries to cache.|
|Struggle to provide data scale and resilience|| Redis Enterprise maintains performance at scale and provides a 99.999% uptime SLA to support mission-critical applications.|