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How to Graph Link Record

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Graph databases are very good at traversing relationships between small data entities, but not ideally suited to store a lot of properties on a single node or large values in those properties.
In computing, a graph database (GDB) is a database that 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).
Neo4j delivers the lightning-fast read and write performance you need, while still protecting your data integrity. It is the only enterprise-strength graph database that combines native graph storage, scalable architecture optimized for speed, and ACID compliance to ensure predictability of relationship-based queries.
Graph data is kept in store files, each of which contain data for a specific part of the graph, such as nodes, relationships, labels and properties. ... Non-native graph databases are not optimized for storing graphs, so the algorithms utilized for writing data may store nodes and relationships all over the place.
Graph databases are NoSQL databases which use the graph data model comprised of vertices, which is an entity such as a person, place, object or relevant piece of data and edges, which represent the relationship between two nodes.
Based upon the concept of a mathematical graph, a graph database contains a collection of nodes and edges. A node represents an object, and an edge represents the connection or relationship between two objects. Each node in a graph database is identified by a unique identifier that expresses key value pairs.
Graph databases are a powerful tool for graph-like queries. For example, computing the shortest path between two nodes in the graph. Other graph-like queries can be performed over a graph database naturally (for example graph's diameter computations or community detection).
Neo4j is an open-source, NoSQL, native graph database that provides an ACID-compliant transactional backend for your applications. Initial development began in 2003, but it has been publicly available since 2007.
Link charts show the magnitude and direction of relationships between two or more categorical variables. They're used in link analysis for identifying relationships between nodes that are not easy to see from the raw data.
By definition, link analysis is a data analysis technique that examines relationships among people, places, and things. As a visual tool, link analysis provides users a powerful method to quickly understand and 'see' what is happening.
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