Essentials are a collection of general-purpose classes we found useful in many occasions. This project is bare bones compared to a rich menu offered by Guava or Apache Commons. Essentials is not a framework, it's rather a small set of utilities to make Java standard approaches more convenient or more efficient.
 
<ul>
<li>IO utilities help with streams (byte and character based) and digests (e.g. MD5 and SHA-1).</li>
<li>File utilities simplify reading and writing strings/bytes/objects from or to files. Also includes getting hashes from files and copying files.</li>
<li>String utilities allow efficient splitting and joining of strings, hex and MD5 creation, and other useful string helpers. Date utilities.</li>
<li>Better hash functions: Murmur3 implementation provides superior hash quality and outperforms standard Java hash functions</li>
<li>Specialized Streams: for example an optimized PipedOutputStream replacement (based on a circular byte buffer)</li>
<li>Hash set and map for primitive long keys outperform the generic versions of the Java Collection APIs</li>
<li>Multimaps provide a map of lists or sets to simplify storing multiple values for a single key</li>
<li>Object cache with powerful configuration options: soft/weak/strong references, maximum size, and time-based expiration</li>
<li>Base64 implementation (bundled from iharder.net) for lower versions of Java &amp; Android (includes input/output streams)</li>
</ul>

Essentials are a collection of general-purpose classes we found useful in many occasions. This project is bare bones compared to a rich menu offered by Guava or Apache Commons. Essentials is not a framework, it's rather a small set of utilities to make Java standard approaches more convenient or more efficient.

Essentials - General purpose utilities and hash functions for Android and Java (aka java-common)

Vavr is an object-functional language extension to Java 8, which aims to reduce the lines of code and increase code quality. It provides persistent collections, functional abstractions for error handling, concurrent programming, pattern matching and much more.
 
Vavr fuses the power of object-oriented programming with the elegance and robustness of functional programming. The most interesting part is a feature-rich, persistent collection library that smoothly integrates with Java's standard collections.

Vavr is an object-functional language extension to Java 8, which aims to reduce the lines of code and increase code quality. It provides persistent collections, functional abstractions for error handling, concurrent programming, pattern matching and much more.

Vavr - Object-functional language extension to Java

A lightning fast, transactional, file-based FIFO for Android and Java. QueueFile is a lightning-fast, transactional, file-based FIFO. Addition and removal from an instance is an O(1) operation and is atomic. Writes are synchronous; data will be written to disk before an operation returns. The underlying file is structured to survive process and even system crashes and if an I/O exception is thrown during a mutating change, the change is aborted.

Tape - A lightning fast, transactional, file-based FIFO for Android and Java.

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

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

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

The main goal of Boon is to reduce the productivity delta between Java and Python/Groovy/Ruby. The idea is to just create a lower ceremony APIs. Less Java like APIs, and more getting things done quickly APIs. If reading a file takes one line of code in Ruby/Python/Groovy, then it will also in Java. If slice notation is part of those language, then Boon will have it to.
 
Boon helps to make lists, maps, and sets feel like they are part of the core language instead of APIs. This includes mimicking map literals, list literals, and set literals. Boon will have its own collection libs. Boon has a collection query language already. It is good alternative to Guava.

The main goal of Boon is to reduce the productivity delta between Java and Python/Groovy/Ruby. The idea is to just create a lower ceremony APIs. Less Java like APIs, and more getting things done quickly APIs. If reading a file takes one line of code in Ruby/Python/Groovy, then it will also in Java. If slice notation is part of those language, then Boon will have it to.



Boon - Low Ceremony. High Productivity. A real boon to Java to developers!

This library provides high-quality Java implementations of mutable and immutable data structures, each sharing a common API. Rather than using the existing collection interfaces in java.util such as List or Map, it provides its own interfaces (IList, IMap, ISet) that provide functional semantics - each update to a collection returns a reference to a new collection. 

bifurcan - impure functional data structures

A Persistent Java Collections Library. PCollections serves as a persistent and immutable analogue of the Java Collections Framework. This includes efficient, thread-safe, generic, immutable, and persistent stacks, maps, vectors, sets, and bags, compatible with their Java Collections counterparts.

PCollections - A Persistent Java Collections Library

Immutable Clojure collections and a Transformation abstraction for Java 8+, immutably, type-safely, and with good performance. It provide support for RRB Tree, which is an immutable List (like Clojure's PersistentVector) that also supports random inserts, deletes, and can be split and joined back together in logarithmic time.

Paguro - Immutable Collections and Functional Transformations for the JVM

javatuples is one of the simplest java libraries ever made. Its aim is to provide a set of java classes that allow you to work with tuples. 
All tuple classes are: 
<UL>
<li>Typesafe</li><li>Immutable</li><li>Iterable</li><li>Serializable</li><li>Comparable (implements <tt>Comparable&lt;Tuple</tt>&gt;)</li><li>Implementing <tt>equals(...)</tt> and <tt>hashCode()</tt></li><li>Implementing <tt>toString()</tt>
</UL>

javatuples is one of the simplest java libraries ever made. Its aim is to provide a set of java classes that allow you to work with tuples.

javatuples - Typesafe representation of tuples in Java.

FastTuple is a library for generating heterogeneous tuples of primitive types from a runtime defined schema without boxing.

FastTuple  - Generates heterogeneous collections of primitive values and ensures as best it can that they will be laid out adjacently in memory

A big, fast and persistent queue based on memory mapped file.
 
Features include: 
<ol>
<li>Fast: close to the speed of direct memory access, both enqueue and dequeue are close to O(1) memory access.</li>
<li>Big: the total size of the queue is only limited by the available disk space.</li>
<li>Persistent: all data in the queue is persisted on disk, and is crash resistant.</li>
<li>Reliable: OS will be responsible to presist the produced messages even your process crashes.</li>
<li>Realtime: messages produced by producer threads will be immediately visible to consumer threads.</li>
<li>Memory-efficient: automatic paging &amp; swapping algorithm, only most-recently accessed data is kept in memory.</li>
<li>Thread-safe: multiple threads can concurrently enqueue and dequeue without data corruption.</li>
<li>Simple&amp;Light-weight: current number of source files is 12 and the library jar is less than 30K.</li>
</ol>

A big, fast and persistent queue based on memory mapped file.

Big Queue - A big, fast and persistent queue based on memory mapped file.

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