Koloboke aims to replace the standard Java collections and streams  with more efficient implementations.  The current version of Koloboke focuses on replacing java.util.HashSet and java.util.HashMap. It provides a complete set of primitive type implementations for each collection. Its able to avoid the expensive boxing/unboxing of primitives and saves memory for boxed primitive objects. It is the fastest and the most memory efficient library implementing hash maps and sets.

Koloboke -   Java Collections till the last breadcrumb of memory and performance

GS Collections is a collections framework for Java. It has JDK-compatible List, Set and Map implementations with a rich API and set of utility classes that work with any JDK compatible Collections, Arrays, Maps or Strings. The iteration protocol was inspired by the Smalltalk collection framework. It provides replacements for ArrayList, HashSet, and HashMap optimized for performance and memory usage.

gs-collections - A supplement or replacement for the Java Collections Framework

Redisson - distributed Java objects and services (Set, Multimap, SortedSet, Map, List, Queue, BlockingQueue, Deque, BlockingDeque, Semaphore, Lock, AtomicLong, Map Reduce, Publish / Subscribe, Bloom filter, Spring Cache, Executor service, Tomcat Session Manager, Scheduler service, JCache API) on top of Redis server. Rich Redis client.
 
Its features include: 
<ul>
<li>Replicated servers mode (also supports <a href="http://docs.aws.amazon.com/AmazonElastiCache/latest/UserGuide/Replication.html">AWS ElastiCache</a> and <a href="https://azure.microsoft.com/en-us/services/cache/">Azure Redis Cache</a>):
<ol>
<li>automatic master server change discovery</li>
</ol>
</li>
<li>Cluster servers mode (also supports <a href="http://docs.aws.amazon.com/AmazonElastiCache/latest/UserGuide/Clusters.html">AWS ElastiCache Cluster</a> and <a href="https://azure.microsoft.com/en-us/services/cache/">Azure Redis Cache</a>):
<ol>
<li>automatic master and slave servers discovery</li>
<li>automatic status and topology update</li>
<li>automatic slots change discovery</li>
</ol>
</li>
<li>Sentinel servers mode:
<ol>
<li>automatic master, slave and sentinel servers discovery</li>
<li>automatic status and topology update</li>
</ol>
</li>
<li>Master with Slave servers mode</li>
<li>Single server mode</li>
<li>Thread-safe implementation</li>
<li><a href="https://github.com/redisson/redisson/wiki/3.-operations-execution#32-reactive-way">Reactive Streams</a> API</li>
<li><a href="https://github.com/redisson/redisson/wiki/3.-operations-execution#31-async-way">Asynchronous</a> API</li>
<li>Asynchronous connection pool</li>
<li>Lua scripting</li>
<li><a href="https://github.com/redisson/redisson/wiki/6.-Distributed-objects">Distributed objects</a> 
Object holder, Binary stream holder, Geospatial holder, BitSet, AtomicLong, AtomicDouble, PublishSubscribe,
Bloom filter, HyperLogLog</li>
<li><a href="https://github.com/redisson/redisson/wiki/7.-Distributed-collections">Distributed collections</a> 
Map, Multimap, Set, List, SortedSet, ScoredSortedSet, LexSortedSet, Queue, Deque, Blocking Queue, Bounded Blocking Queue, Blocking Deque, Delayed Queue, Priority Queue, Priority Deque</li>
<li><a href="https://github.com/redisson/redisson/wiki/8.-Distributed-locks-and-synchronizers">Distributed locks and synchronizers</a> 
Lock, FairLock, MultiLock, RedLock, ReadWriteLock, Semaphore, PermitExpirableSemaphore, CountDownLatch</li>
<li><a href="https://github.com/redisson/redisson/wiki/9.-distributed-services">Distributed services</a> 
Remote service, Live Object service, Executor service, Scheduler service, MapReduce service</li>
<li><a href="https://github.com/redisson/redisson/wiki/14.-Integration%20with%20frameworks/#141-spring-cache">Spring Cache</a> implementation &nbsp;</li>
<li><a href="https://github.com/redisson/redisson/wiki/14.-Integration%20with%20frameworks/#142-hibernate-cache">Hibernate Cache</a> implementation</li>
<li><a href="https://github.com/redisson/redisson/wiki/14.-Integration%20with%20frameworks/#143-jcache-api-jsr-107-implementation">JCache API (JSR-107)</a> implementation</li>
<li><a href="https://github.com/redisson/redisson/wiki/14.-Integration%20with%20frameworks#144-tomcat-redis-session-manager">Tomcat Session Manager</a> implementation</li>
<li><a href="https://github.com/redisson/redisson/wiki/14.-Integration%20with%20frameworks/#145-spring-session">Spring Session</a> implementation</li>
<li><a href="https://github.com/redisson/redisson/wiki/10.-additional-features#102-execution-batches-of-commands">Redis pipelining</a> (command batches)</li>
<li>Supports Android platform</li>
<li>Supports auto-reconnection</li>
<li>Supports failed to send command auto-retry</li>
<li>Supports OSGi</li>
<li>Supports SSL</li>
<li>Supports many popular codecs (<a href="https://github.com/FasterXML/jackson">Jackson JSON</a>, <a href="http://avro.apache.org/">Avro</a>, <a href="http://wiki.fasterxml.com/SmileFormatSpec">Smile</a>, <a href="http://cbor.io/">CBOR</a>, <a href="http://msgpack.org/">MsgPack</a>, <a href="https://github.com/EsotericSoftware/kryo">Kryo</a>, <a href="https://amzn.github.io/ion-docs/">Amazon Ion</a>, <a href="https://github.com/RuedigerMoeller/fast-serialization">FST</a>, <a href="https://github.com/jpountz/lz4-java">LZ4</a>, <a href="https://github.com/xerial/snappy-java">Snappy</a> and JDK Serialization)</li>
<li>With over 1000 unit tests</li>
</ul>

Redisson - distributed Java objects and services (Set, Multimap, SortedSet, Map, List, Queue, BlockingQueue, Deque, BlockingDeque, Semaphore, Lock, AtomicLong, Map Reduce, Publish / Subscribe, Bloom filter, Spring Cache, Executor service, Tomcat Session Manager, Scheduler service, JCache API) on top of Redis server. Rich Redis client.

Redisson - Redis based In-Memory Data Grid for Java

Capsule aims to become a full-fledged (immutable) collections library for Java 8+ that is solely built around persistent tries. The library is designed for standalone use and for being embedded in domain-specific languages. Capsule still has to undergo some incubation before it can ship as a well-rounded collection library. Nevertheless, the code is stable and performance is solid.
 
The standard libraries of recent Java Virtual Machine languages, such as Clojure or Scala, contain scalable and well-performing immutable collection data structures that are implemented as Hash-Array Mapped Tries (HAMTs). HAMTs already feature efficient lookup, insert, and delete operations, however due to their tree-based nature their memory footprints and the runtime performance of iteration and equality checking lag behind array-based counterparts.
 
We introduce CHAMP (Compressed Hash-Array Mapped Prefix-tree), an evolutionary improvement over HAMTs. The new design increases the overall performance of immutable sets and maps. Furthermore, its resulting general purpose design increases cache locality and features a canonical representation.

Capsule aims to become a full-fledged (immutable) collections library for Java 8+ that is solely built around persistent tries. The library is designed for standalone use and for being embedded in domain-specific languages. Capsule still has to undergo some incubation before it can ship as a well-rounded collection library. Nevertheless, the code is stable and performance is solid.

Capsule - The Capsule Hash Trie Collections Library

SmoothieMap is a Map implementation for Java with the lowest memory usage and absence of rehash latency spikes. Under the hood, it is a version of extendible hashing with 48-slot mini segments. This project also includes a proof-of-concept implementation of SwissTable algorithm in Java.



SmoothieMap - A gulp of low latency Java HashMap

HPPC provides template-generated implementations of typical collections, such as lists, sets and maps, for all Java primitive types. The primary driving force behind HPPC is optimization for highest performance and memory efficiency. 

HPPC - High Performance Primitive Collections for Java

Caffeine is an awesome Java caching library. It has an impressive performance and a neat Java 8 API. However the API does not play very well with Scala. So this is the thinner wrapper we can came with to make Caffeine easy and idiomatic to use in Scala.

scaffeine - Thin Scala wrapper for Caffeine

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Koloboke - Java Collections till the last breadcrumb of memory and performance

gs-collections - A supplement or replacement for the Java Collections Framework

Redisson - Redis based In-Memory Data Grid for Java

Capsule - The Capsule Hash Trie Collections Library

SmoothieMap - A gulp of low latency Java HashMap

HPPC - High Performance Primitive Collections for Java

scaffeine - Thin Scala wrapper for Caffeine

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Koloboke - Java Collections till the last breadcrumb of memory and performance

gs-collections - A supplement or replacement for the Java Collections Framework

Redisson - Redis based In-Memory Data Grid for Java

Capsule - The Capsule Hash Trie Collections Library

SmoothieMap - A gulp of low latency Java HashMap

HPPC - High Performance Primitive Collections for Java

scaffeine - Thin Scala wrapper for Caffeine

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