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Chronicle Map - High performance, off-heap, key-value, in memory, persisted data store
Chronicle Map is a high performance, off-heap, key-value, in memory, persisted data store. It works like a standard java map yet it automatically distributes data between processes, these processes can be both on the same server or across your network. In other words its a low latency, huge data key value store, which can store terabytes of data locally to your process.
Memcached is high-performance, distributed memory object caching system, generic in nature, but intended for use in speeding up dynamic web applications by alleviating database load. Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
Infinispan is an extremely scalable, highly available key/value NoSQL datastore and distributed data grid platform. The purpose of Infinispan is to expose a data structure that is highly concurrent, designed ground-up to make the most of modern multi-processor/multi-core architectures while at the same time providing distributed cache capabilities. Infinispan offers enterprise features such as efficient eviction algorithms to control memory usage as well as JTA compatibility.
Ehcache is an open source, standards-based cache used to boost performance, offload the database and simplify scalability. Ehcache is robust, proven and full-featured and this has made it the most widely-used Java-based cache.
Redis is an advanced key-value store. It is similar to memcached but the dataset is not volatile, and values can be strings, exactly like in memcached, but also lists, sets, and ordered sets. All this data types can be manipulated with atomic operations to push/pop elements, add/remove elements, perform server side union, intersection, difference between sets, and so forth. Redis supports different kind of sorting abilities.
HyperDex is a distributed, searchable key-value store. HyperDex provides a unique search primitive which enables searches over stored values. By design, HyperDex retains the performance of traditional key-value stores while enabling support for the search operation. It is fast, scalable, Consistent, Fault tolerant.
Voldemort is a distributed key-value storage system. Data is automatically replicated over multiple servers. Data is automatically partitioned so each server contains only a subset of the total data.
Server failure is handled transparently. It is used at LinkedIn for certain high-scalability storage problems where simple functional partitioning is not sufficient.
Oracle Berkeley DB provides the best open source embeddable databases allowing developers the choice of SQL, Key/Value, XML/XQuery or Java Object storage for their data model. At its core is a fast, scalable, transactional database engine with proven reliability and availability. Berkeley DB comes three versions: Berkeley DB, Berkeley DB Java Edition, and Berkeley DB XML.
Membase is an distributed, key-value database management system optimized for storing data behind interactive web applications. These applications must service many concurrent users, creating, storing, retrieving, aggregating, manipulating and presenting data in real-time. Supporting these requirements, membase processes data operations with quasi-deterministic low latency and high sustained throughput.
Dynomite, inspired by Dynamo whitepaper, is a thin, distributed dynamo layer for different storages and protocols. Dynomite is a sharding and replication layer. Dynomite can make existing non distributed datastores, such as Redis or Memcached, into a fully distributed & multi-datacenter replicating datastore.
JCS is a distributed caching system written in java. It is intended to speed up applications by providing a means to manage cached data of various dynamic natures. Its feature include Memory management, Element grouping, Data expiration, UDP Discovery of other caches, Key pattern matching retrieval, Remote server chaining (or clustering) and failover, Remote synchronization, Region data separation and configuration and lot more.