A single Redis cluster can be used to do any of these ten things, regardless of whether it’s a transactional or analytical workload.
- Use it as your primary database : Redis is not just a NoSQL database. It goes well beyond NoSQL to implement numer-ous features for today’s enterprise customers. Redis is more than simple key/value storage — it provides multiple data models and multiple methods to access data.Redis can be utilized by the entire application stack within an organization.
- Cache most frequently used pieces of data: Load data from slower data sources into Redis and provide near-instant response times. Redis keeps data in random access memory (RAM) to make retrieval fast.
- Use it for session storage: Session storage requires very fast response times, both for writing data as users progress through an application and for reading that information back. Redis is an excellent fit for session storage due to its native data-type storage that mirrors the kind of storage needed for storing session data
- Decouple services: Redis streams and the publish/subscribe pattern enable service decoupling. Services can write to and read from Redis streams or can publish and subscribe send messages using Redis as the facilitator of the pub/sub pattern.
- Provide rate limiting: Redis can be used to rate-limit users and endpoints. The high-performance, real-time nature of Redis means that tracking can be done in real time along with the users and endpoints.
- Ingest data quickly: Redis is known for its capability to work with large amounts of data at speed. Consuming or taking in data in large quantities and then processing it or handing it off for further processing makes Redis a great choice for data ingest.
- Build real-time leaderboards: Native data types that promote sorting and counting operations enable Redis to be used as the back end for real-time leaderboards.
- Build a store finder: Redis includes GEO-based data types that natively handle geospatial data like latitude and longitude calculations. A store finder is another use case where Redis is the compelling solution.
- Perform analytics efficiently: Data that needs to be processed can be stored in Redis in a compact manner. Data that may take terabytes in another storage medium can be processed in such a way that it requires significantly less resources when you use Redis. For example, probabilistic data structures can be used that then help to maintain counts, frequencies, and percentiles very efficiently.
- Index large amounts of data: Redis handles large amounts of data well. As an organization and its application portfolio grow, so does the amount of data. Redis has the flexibility and extensibility (through modules) to store data for multiple consumers and the performance and efficiency to store large amounts of data for established and new organizations alike.
I got this ten use cases of Redis after i read Redis for dummies - limited Edition.
I'll be genuinely pleasure if you like or share the article. thanks ^^