Goque provides embedded, disk-based implementations of stack and queue data structures. Motivation for creating this project was the need for a persistent priority queue that remained performant while growing well beyond the available memory of a given machine. While there are many packages for Go offering queues, they all seem to be memory based and/or standalone solutions that are not embeddable within an application.

goque - Persistent stacks and queues for Go backed by LevelDB

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

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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goque - Persistent stacks and queues for Go backed by LevelDB

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

Redisson - Redis based In-Memory Data Grid for Java

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

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goque - Persistent stacks and queues for Go backed by LevelDB

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

Redisson - Redis based In-Memory Data Grid for Java

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

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