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  2. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Graph databases portray the data as it is viewed conceptually. This is accomplished by transferring the data into nodes and its relationships into edges. A graph database is a database that is based on graph theory. It consists of a set of objects, which can be a node or an edge.

  3. InfiniteGraph - Wikipedia

    en.wikipedia.org/wiki/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.

  4. Multi-model database - Wikipedia

    en.wikipedia.org/wiki/Multi-model_database

    NoSQL databases use a variety of data models, with document, graph, and key–value models being popular. [2] A multi-model database is a database that can store, index and query data in more than one model. For some time, databases have primarily supported only one model, such as: relational database, document-oriented database, graph database ...

  5. OrientDB - Wikipedia

    en.wikipedia.org/wiki/OrientDB

    OrientDB is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document and object models, [2] the relationships are managed as in graph databases with direct connections between records. It supports schema-less, schema-full and schema-mixed modes.

  6. NoSQL - Wikipedia

    en.wikipedia.org/wiki/NoSQL

    The data structures used by NoSQL databases (e.g. key–value pair, wide column, graph, or document) are different from those used by default in relational databases, making some operations faster in NoSQL. The particular suitability of a given NoSQL database depends on the problem it must solve.

  7. Ontotext - Wikipedia

    en.wikipedia.org/wiki/Ontotext

    Ontotext GraphDB (previously known as BigOWLIM) is a graph-based database [6] capable of working with knowledge graphs [7] produced by Ontotext, compliant with the RDF graph data model [8] and the SPARQL query language. [9] Some categorize it as a NoSQL database, meaning that it does not use tables like some other databases. [10]

  8. Cypher (query language) - Wikipedia

    en.wikipedia.org/wiki/Cypher_(query_language)

    There are two graph models in current use: the Resource Description Framework (RDF) model and the Property Graph model. The RDF model has been standardized by W3C in a number of specifications. The Property Graph model, on the other hand, has a multitude of implementations in graph databases, graph algorithms, and graph processing facilities.

  9. List of in-memory databases - Wikipedia

    en.wikipedia.org/wiki/List_of_in-memory_databases

    ArangoDB is a transactional native multi-model database supporting two major NoSQL data models (graph and document [1]) with one query language. Written in C++ and optimized for in-memory computing. In addition ArangoDB integrated RocksDB for persistent storage. ArangoDB supports Java, JavaScript, Python, PHP, NodeJS, C++ and Elixir.