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.

Project-voldemort - A distributed database, Clone of Amazon's Dynamo

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. Its features include: 
 <UL>
	<LI>Fast and Light Weight</LI>
	<LI>Scalable to hundreds of caches</LI>
	<LI>Multiple CacheManagers per virtual machine</LI>
	<LI>Distributed Caching</LI>
	<LI>Provides LRU, LFU and FIFO cache eviction policies</LI>
	<LI>Supports Object or Serializable caching</LI>
	<LI>Full implementation of JSR107 JCACHE API</LI>
	<LI>Extensible</LI>
	<LI>Persistence, Flush to disk on demand</LI>
	<LI>Supports as standalone server, SOAP cache server, RESTful cache server</LI>
	<LI>Works with Hibernate, Google App Engine </LI>
 </UL>

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.

Ehcache

OrientDB has the flexibility of the Document databases and the power of the Graph databases to manage relationships. It can work in schema-less mode, schema-full or a mix of both. It can store up to 150,000 records per second on common hardware. OrientDB has been designed to be very fast. It inherits the best features and concepts from the Object Databases, Graph DBMS and the modern NoSQL engines. 
 Source code location: <A HREF="http://code.google.com/p/orient/" target="_blank">http://code.google.com/p/orient/</A>

OrientDB has the flexibility of the Document databases and the power of the Graph databases to manage relationships. It can work in schema-less mode, schema-full or a mix of both. It can store up to 150,000 records per second on common hardware. OrientDB has been designed to be very fast. It inherits the best features and concepts from the Object Databases, Graph DBMS and the modern NoSQL engines.

OrientDB - The NoSQL Graph-Document DBMS

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.

Apache Commons JCS - Java Caching System

Caffeine is a high performance, near optimal caching library based on Java 8. It provides an in-memory cache using a Google Guava inspired API.
 
<ul>
<li><a href="https://github.com/ben-manes/caffeine/wiki/Population">automatic loading of entries</a> into the cache, optionally asynchronously</li>
<li><a href="https://github.com/ben-manes/caffeine/wiki/Eviction#size-based">size-based eviction</a> when a maximum is exceeded based on <a href="https://github.com/ben-manes/caffeine/wiki/Efficiency">frequency and recency</a></li>
<li><a href="https://github.com/ben-manes/caffeine/wiki/Eviction#time-based">time-based expiration</a> of entries, measured since last access or last write</li>
<li><a href="https://github.com/ben-manes/caffeine/wiki/Refresh">asynchronously refresh</a> when the first stale request for an entry occurs</li>
<li>keys automatically wrapped in <a href="https://github.com/ben-manes/caffeine/wiki/Eviction#reference-based">weak references</a></li>
<li>values automatically wrapped in <a href="https://github.com/ben-manes/caffeine/wiki/Eviction#reference-based">weak or soft references</a></li>
<li><a href="https://github.com/ben-manes/caffeine/wiki/Removal">notification</a> of evicted (or otherwise removed) entries</li>
<li><a href="https://github.com/ben-manes/caffeine/wiki/Writer">writes propagated</a> to an external resource</li>
<li>accumulation of cache access <a href="https://github.com/ben-manes/caffeine/wiki/Statistics">statistics</a></li>
</ul>

Caffeine is a high performance, near optimal caching library based on Java 8. It provides an in-memory cache using a Google Guava inspired API.

Caffeine -  A high performance caching library for Java 8

The Apache Accumulo sorted, distributed key/value store is a robust, scalable, high performance data storage and retrieval system. Apache Accumulo is based on Google's BigTable design and is built on top of Apache Hadoop, Zookeeper, and Thrift. Apache Accumulo features a few novel improvements on the BigTable design in the form of cell-based access control and a server-side programming mechanism that can modify key/value pairs at various points in the data management process.

Apache Accumulo - Key Value Store based on Google BigTable

Apache Ignite In-Memory Data Fabric is a high-performance, integrated and distributed in-memory platform for computing and transacting on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based or flash technologies. 
 
Apache Ignite has advanced compute and clustering capabilities including Dynamic Sub-Clusters, Clustered Lambda Execution, Clustered ForkJoin Tasks.

Apache Ignite In-Memory Data Fabric is a high-performance, integrated and distributed in-memory platform for computing and transacting on large-scale data sets in real-time, orders of magnitude faster than possible with traditional disk-based or flash technologies. 


Apache Ignite - High performance in-memory data grid

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.

Chronicle Map - High performance, off-heap, key-value, in memory, persisted data store

MapDB is an embedded database engine. It provides Maps and other collections backed by disk or memory storage. It offers excellent performance comparable to java collections, but is not limited by GC overhead. It is also a full database engine with storage backends, transactions, cache algorithms, expiration and many other options. MapDB provides concurrent Maps, Sets and Queues backed by disk storage or off-heap memory. 

MapDB - Embedded Database Engine

cache2k focuses on providing a well engineered in-memory object cache implementation for Java applications. It has fastest access times, due to non blocking and wait free access of cached values. It is thread safe, with a complete set of atomic operations. It supports automatic expiry and refresh: duration or point in time, variable expiry per entry, delta calculations.

Cache2k –  Lightweight, high performance Java caching 

Apache Geode  is distributed, in-memory database for scale-out applications. All data is stored in-memory for low latency. Performance scales linearly as nodes are added. Data is distributed automatically between nodes to optimize performance. Clusters fail-over to other nodes in case of failures, and rebalance remaining resources. Geode servers can be configured to talk memcached protocol. 

Apache Geode - Distributed, In-memory Database for Scale-Out Applications

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