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Features * The data is always stored in-memory (RAM) of the servers
* Multiple copies are stored in multiple machines for automatic data recovery in case of single or multiple server failures
* The data model is object-oriented and non-relational
* Servers can be dynamically added or removed to increase the amount of CPU and RAM
* The data can be persisted from Hazelcast to a relational or NoSQL database
* A Java Map API accesses the distributed key-value store
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Features * Local, Invalidation, Replicated and Distributed cache modes
* Multiple discovery algorithms for elastic node provisioning
* Partition handling detects split brain scenarios and reduces availability to provide consistency in such situations
* Store immortal and mortal entries in the same cache
* Entry mortality defined by lifespan or maximum idle time
* Define the maximum number of entries to be kept in memory
* Define the maximum size of entries to be kept in memory
* Concurrency control based on Optimistic and pessimistic locks and total order
* Support for XA and synchronization models
* Synchronous and asynchronous indexing engine
* Lucene-based indexing powered by Hibernate Search
* Clustering authentication and authorization integrated with the Security Realms in the server.
* Distributed streams based on java.util.stream
* High-performance multi-threaded Map/Reduce
* Distributed executor
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LanguagesCPP Java VB.NET Python Other |
LanguagesCPP Java Python Other |
Source TypeOpen
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Source TypeOpen
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License TypeProprietary |
License TypeOther |
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Pricing
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Pricing
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