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Gremlin (programming Language)
Gremlin is a graph traversal language and virtual machine developed by Apache TinkerPop of the Apache Software Foundation. Gremlin works for both OLTP-based graph databases as well as OLAP-based graph processors. Gremlin's automata and functional language foundation enable Gremlin to naturally support: imperative and declarative querying; host language agnosticism; user-defined domain specific languages; an extensible compiler/optimizer, single- and multi-machine execution models; hybrid depth- and breadth-first evaluation with Turing completeness. As an explanatory analogy, Apache TinkerPop and Gremlin are to graph databases what the JDBC and SQL are to relational databases. Likewise, the Gremlin traversal machine is to graph computing as what the Java virtual machine is to general purpose computing. History * 2009-10-30 the project is born, and immediately named "TinkerPop" * 2009-12-25 v0.1 is the first release * 2011-05-21 v1.0 is released * 2012-05-24 v2.0 is rele ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Domain-specific Language
A domain-specific language (DSL) is a computer language specialized to a particular application domain. This is in contrast to a general-purpose language (GPL), which is broadly applicable across domains. There are a wide variety of DSLs, ranging from widely used languages for common domains, such as HTML for web pages, down to languages used by only one or a few pieces of software, such as MUSH soft code. DSLs can be further subdivided by the kind of language, and include domain-specific ''markup'' languages, domain-specific ''modeling'' languages (more generally, specification languages), and domain-specific ''programming'' languages. Special-purpose computer languages have always existed in the computer age, but the term "domain-specific language" has become more popular due to the rise of domain-specific modeling. Simpler DSLs, particularly ones used by a single application, are sometimes informally called mini-languages. The line between general-purpose languages and doma ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
JanusGraph
JanusGraph is an open source, distributed graph database under The Linux Foundation. JanusGraph is available under the Apache License 2.0. The project is supported by IBM, Google, Hortonworks and Grakn Labs. JanusGraph supports various storage backends (Apache Cassandra, Apache HBase, Google Cloud Bigtable, Oracle BerkeleyDB, ScyllaDB). The Scalability of JanusGraph depends on the underlying technologies, which are used with JanusGraph. For example, by using Apache Cassandra as a storage backend scaling to multiple datacenters is provided out of the box. JanusGraph supports global graph data analytics, reporting, and ETL through integration with big data platforms (Apache Spark, Apache Giraph, Apache Hadoop). JanusGraph supports geo, numeric range, and full-text search via external index storages (ElasticSearch, Apache Solr, Apache Lucene Apache Lucene is a free and open-source search engine software library, originally written in Java by Doug Cutting. It is supported ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
InfiniteGraph
InfiniteGraph is a distributed graph database implemented in Java and C++ and is from a class of NOSQL ("Not Only SQL") database technologies that focus on graph data structures. Developers use InfiniteGraph to find useful and often hidden relationships in highly connected, complex big data sets. InfiniteGraph is cross-platform, scalable, cloud-enabled, and is designed to handle very high throughput. InfiniteGraph can easily and efficiently perform queries that are difficult to perform, such as finding all paths or the shortest path between two items. InfiniteGraph is suited for applications and services that solve graph problems in operational environments. InfiniteGraphs "DO" query language enables both value-based queries and complex graph queries. InfiniteGraph goes beyond graph databases to also support complex object queries. Adoption is seen in federal government, telecommunications, healthcare, cybersecurity, manufacturing, finance, and networking applications. History I ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Spark
Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of California, Berkeley's AMPLab starting in 2009, in 2013, the Spark codebase was donated to the Apache Software Foundation, which has maintained it since. Overview Apache Spark has its architectural foundation in the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. The Dataframe API was released as an abstraction on top of the RDD, followed by the Dataset API. In Spark 1.x, the RDD was the primary application programming interface (API), but as of Spark 2.x use of the Dataset API is encouraged even though the RDD API is not deprecated. The RDD technology still underlies the Dataset API. Spark and its RDDs were developed in 2012 in respon ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Apache Giraph
Apache Giraph is an Apache Software Foundation, Apache project to perform Graph (computer science), graph processing on big data. Giraph utilizes Apache Hadoop's MapReduce implementation to process graphs. Facebook used Giraph with some performance improvements to analyze one trillion edges using 200 machines in 4 minutes. Giraph is based on a paper published by Google about its own graph processing system called Pregel. It can be compared to other Big Graph processing libraries such as Cassovary. As of September 2023, it is no longer actively developed. References External links * {{DEFAULTSORT:Giraph Apache Software Foundation projects, Giraph Hadoop Data mining and machine learning software ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
