mrniko/redisson
Redisson
Redisson is a Java client library for Redis and Valkey that provides a distributed data structure library, a distributed lock manager, and a distributed MapReduce framework. It enables application instances in a cluster to share state through thread-safe collections and objects.
The project implements a JCache compliant caching layer for standardized data storage and retrieval. It also functions as a probabilistic data store, providing memory-efficient structures such as Bloom filters and HyperLogLog for high-volume data membership testing.
The library covers distributed state management using shared maps, sets, and queues, as well as distributed task scheduling for background jobs and atomic counters. It further supports externalized web session management and the parallel processing of large datasets through distributed MapReduce.
Features
- Distributed Collections - Implements distributed thread-safe maps, sets, lists, and queues for sharing state between application nodes.
- Distributed State Management - Implements shared maps, sets, and queues to maintain consistent application state across a cluster.
- Distributed State Structures - Synchronizes application state using distributed maps, sets, queues, and locks stored remotely.
- Remote Object Mappings - Maps local Java object methods to remote Redis commands through a specialized serialization layer.
- Redis Clients - Acts as a comprehensive Java client library for interacting with Redis and Valkey data stores.
- Atomic Counters - Generates consistent atomic counters and IDs across a network using distributed numeric values.
- Distributed Locks - Provides distributed lock coordination to ensure mutual exclusion across a cluster of application instances.
- Distributed Collections - Provides a comprehensive set of thread-safe distributed collections for sharing state across cluster nodes.
- Cache API Implementations - Provides a JCache compliant caching layer for standardized data storage and retrieval.
- Caching - Combines remote data stores with local caches to reduce network latency for frequent reads.
- Distributed Sharding Architectures - Implements data sharding to distribute large datasets across multiple Redis nodes for horizontal scaling.
- MapReduce Processing Engines - Provides a distributed MapReduce framework to process large datasets in parallel across multiple nodes.
- Probabilistic Data Structures - Implements memory-efficient probabilistic structures like Bloom filters and HyperLogLog for high-volume membership testing.
- Probabilistic Membership Filters - Ships memory-efficient probabilistic structures like Bloom filters for high-volume data membership testing.
- Server-Side Scripting - Uses server-side Lua scripting to execute complex atomic operations directly within the data store.
- Distributed Task Schedulers - Coordinates background processing across a network by executing scheduled jobs and managing distributed atomic counters.
- Task Schedulers - Provides a distributed executor service to run scheduled jobs and remote services across a cluster.
- Standardized Caching APIs - Implements a JCache compliant caching layer for standardized data storage and retrieval.
- Tiered Caching - Implements a multi-tier caching strategy combining local in-memory storage with a remote data store.
- Distributed Task Schedulers - Coordinates distributed tasks and background processing across a network using remote scheduling.
- Pub-Sub Messaging - Coordinates reliable message delivery using topics and sharded topics via a pub/sub architecture.
- Event-Driven Synchronization - Synchronizes local application state by listening to real-time publication channels via a pub/sub mechanism.
- Event-Driven I/O - Utilizes a Netty-based event-driven I/O framework to handle high-concurrency asynchronous network communication.
- Session Managers - Externalizes web session state to a remote store to enable horizontal scaling and failover.
- Database Clients and Drivers - Distributed Java objects and services for Redis.
- Cluster Management and Elasticity - Distributed and scalable data structures for Redis.
