Graph Databases

Graph Database is a database structure that uses graphs to map, store and query relationships with nodes, edges and properties to represent and store the data. Graph Database uses graph structures for semantic queries with nodes, edges and properties to represent and store data. A key concept of the system is the graph (or edge or relationship), which directly relates data items in the store. Some uses a relational engine and which stores the graph data on a table while others uses a document-oriented or key value store database for storage. Data can be retrieved from graph data base using a query language or an application programming language (API). The implementation of graph database is based on graph theory and employs nodes, edges and properties. Each node signifies an entity like a firm, individual or organization or targeted item to be tracked. The nodes are connected by Edges (lines) which are also referred to as graphs or relationship. The edges present a meaningful pattern that picture out the interconnections and connections of the nodes, properties and edges. The nodes are defined by a unique key/value which is referred to as the properties. It is faster for associative data set and conforms more directly to the structure of object-oriented applications. Graph database directly stores the relationships of nodes between records.

PAT Grid™ for Graph Databases

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Graph Databases
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Top Five
PAT Index™
 
1
ArangoDB
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2
Neoj
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3
OrientDB
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4
AllegroGraph
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5
Ontotext GraphDB
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