Partitioning in Redis
Redis provides horizontal partitioning (sharding) for distributing data across multiple instances. This is useful for handling large datasets and achieving high throughput. Each shard (instance) is responsible for a subset of the keys, and Redis Cluster provides built-in support for partitioning. It is used to distribute data across multiple Redis instances (also known as nodes) to improve performance, scalability, and fault tolerance. Instead of relying on a single Redis server, partitioning allows you to divide your dataset and workloads among several Redis nodes, enabling you to harness the combined processing power of these nodes.
How does Redis store data?
Redis is an in-memory data store. It stores data primarily in RAM, allowing extremely fast read and write operations. The data is organized using key-value pairs, where keys are unique identifiers, and values can be of different types, including strings, lists, sets, sorted sets, hashes, bitmaps, and more. Data in Redis is accessed by keys, making it a highly efficient and simple data store.
Important Topics for How Redis Stores data
- Data Structures in Redis
- Persistence Options in Redis
- Partitioning in Redis
- Virtual Memory in Redis
- Data Eviction