Search results for 'open source email campaign'
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HyperGraphDB
HyperGraphDB– An Open Source Graph Database
HyperGraphDB is an open source Graph Database based on a powerful knowledge management formalism known as directed hypergraphs. It can be used as an embedded object-oriented database for Java projects or as a NoSQL relational database. The core of the database engine is designed for generalized, typed and directed hypergraphs.
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Gremlin
Gremlin – An Open Source Graph Database
Gremlin is a graph traversal language and it can be used for graph analysis, query and manipulation. Gremlin works with the graph databases that have included the Blueprints property graph data model. These include among others Neo4j, OrientDB, and Infinite Graph. Gremlin provides native support for Java and Groovy.
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Gora
GORA – An Open Source In-memory Computing Tool
The Apache Gora is an open source framework which provides an in-memory data model and persistence for big data. Gora supports persisting to column stores, key value stores, document stores and RDBMSs, and analyzing the data with extensive Apache Hadoop MapReduce support.
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GridGain
GRIDGAIN- An Open Source In-memory Computing Tool
GridGain’s open source software provides immediate, unhindered freedom to develop with the most mature, complete and tested in-memory computing platform on the market, enabling computation and transactions orders of magnitude faster than traditional technologies allow. From high performance computing, streaming and data grid to an industry first in-memory Hadoop accelerator, GridGain provides a complete end-to-end stack for low-latency, high performance computing for each and every category of payload and data processing requirements.
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Hazelcast
Hazelcast– An Open Source In-memory Computing Tool
Hazelcast, an open source clustering and highly scalable data distribution platform written in Java, focuses on latency and makes it easier to cache/share/operate TB's of data in-memory. Storing terabytes of data in-memory is not a problem but avoiding GC to achieve predictable, low latency and being resilient to crashes are big challenges. By default, Hazelcast stores your distributed data (map entries, queue items) into Java heap which is subject to garbage collection. As your heap gets bigger, garbage collection might cause your application to pause tens of seconds, badly affecting your application performance and response times. Elastic Memory is Hazelcast with off-heap memory storage to avoid GC pauses. Even if you have terabytes of cache in-memory with lots of updates, GC will have almost no effect; resulting in more predictable latency and throughput.
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