15 Reasons to use Redis as an Application Cache
Redis as an application cache is undoubtedly a good way to improve application performance. By definition, caching is a technique used to accelerate application response times and help applications scale by placing frequently needed data very close to the application.
Redis, an open source, in-memory, data structure server is frequently used as a distributed shared cache (in addition to being used as a message broker or database). This is possible because it enables true statelessness for an applications’ processes, while reducing duplication of data or requests to external data sources. Check out some reasons that become Redis an ideal caching solution for every application.
What is an application cache
Once an application process uses an external data source, its performance can be bottlenecked by the throughput and latency of said data source. So when a slower external data source is used, frequently accessed data is often moved temporarily to a faster storage that is closer to the application to boost the application’s performance.
This faster intermediate data storage is called the application’s cache, a term originating from the French verb “cacher” which means “to hide.” The following diagram shows the high-level architecture of an application cache:
Missing cache data fetched from the source and cached
What is in the cache
An application’s cache is intended for storing data that the application’s process requires rapidly during execution. Though each application is unique and can potentially store any kind of data in its cache, an application would typically use a cache for:
- Configuration settings;
- Localization and internationalization data;
- Templates and partially rendered responses;
- Reusable results of compute-intensive functions;
- Session data;
- DBMS data;
- API responses; and
- Application objects.
Redis as a distributed shared cache
Redis is an open source, in-memory Data Structure Store, used as a database, a caching layer or a message broker. Sometimes referred to as the “Leatherman of Databases”, it’s simple yet flexible design philosophy makes it an effective choice for solving a multitude of demanding data processing tasks.
Certainly Redis data structures resolve very complex programming problems with simple commands executed within the data store, reducing coding effort, increasing throughput, and reducing latency.
Caching is one of Redis’ most popular use cases as Redis perfectly meets the requirements of an application’s distributed caching layer.
15 Reasons to use Redis as an Application Cache
Following are 15 reasons to use Redis as an application cache:
- In-memory store: All data in Redis is stored in RAM, delivering the fastest possible access times to the data for both read and write requests.
- Optimized for speed: Redis is designed and implemented for performance. Being written in ANSI C, it compiles into extremely efficient machine code and requires little overhead.
- Support for arbitrary data: Data stored in Redis can be in any form and size. Redis is binary safe so it can store any data, from human readable text to encoded binaries.
- Key-based access: Redis is based on the key-value model in which data is stored and fetched from Redis by key.
- Multi-key operations: Multi-key operations provide better overall performance compared to performing the operations one after the other, because they require substantially less communication and administration.
- Atomicity of operations and transactions: This ensures the integrity of the cached data and provides a consistent view of it to the processes sharing it.
- Data expiration: Keys in Redis can be set with a time to live (TTL), after which they are expired. Until they expire, such keys are called “volatile” keys.
- Eviction policies: When used as a cache, Redis supports a configurable eviction policy that is triggered when its memory is running low. Because cached data is ephemeral, it is possible to evict the existing data that is in the cache to make room for new data.
- Intelligent caching: Redis’ true value is providing advanced data structures and operations to application developers. “Intelligent caching” exploits their unique properties to efficiently and optimally manipulate data.
- Distributed network server: Redis is designed to be a remote, network-attached server. It uses a lightweight TCP protocol that has client implementations in every conceivable programming language.
- Request pipelining: To reduce the penalties incurred by sending many small packets over the network, and in cases where the multiple requests need to be sent to the cache without waiting for responses, the Redis protocol supports a pipelining mode.
- Highly available: A cache is only effective if it is available to the application. The data in Redis and the service that Redis provides can be made highly available via the use of Redis’ built-in replication mechanism.
- Data persistence: Despite cached data’s temporary existence, it is sometimes desirable for the cache to persist data to durable storage when cached data is relatively static or for faster recovery times from outages by allowing a swift recovery of the cache.
- Scalable shared-nothing clustering: Redis can be scaled horizontally to meet any increase in demand for RAM, computation or network resources.
- Local cache replicas: Redis can be deployed on the same server that runs the application’s processes in order to act as a local private cache.
The distributed cache is a widely-adopted design pattern for building robust and scalable applications. By serving data from the cache, and instead of fetching it from slower devices or re-computing it, the application’s overall performance is improved.
The cache also relieves some of the load on external data sources as well as improves the availability of the application during outages. Redis is the most popular distributed caching engine today. It is production-proven and provides a host of capabilities that make it the ideal distributed caching layer for applications.
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