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Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
GraphRAG [40] (coined by Microsoft Research) is a technique that extends RAG with the use of a knowledge graph (usually, LLM-generated) to allow the model to connect disparate pieces of information, synthesize insights, and holistically understand summarized semantic concepts over large data collections. It was shown to be effective on datasets ...
NebulaGraph was developed in 2018 by Vesoft Inc. [3] In May 2019, NebulaGraph made free software on GitHub and its alpha version was released same year. [4]In June 2020, NebulaGraph raised $8M in a series pre-A funding round led by Redpoint China Ventures and Matrix Partners China.
The resulting graph is a property graph, which is the underlying graph model of graph databases such as Neo4j, JanusGraph and OrientDB where data is stored in the nodes and edges as key-value pairs. In effect, code property graphs can be stored in graph databases and queried using graph query languages.
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]
Rule-based or agent-based tool selection determines the access pattern to use: a) Search - text from the lexical graph is searched using keyword, full-text, or vector similarity search b) Search + pattern match - following a search, graph pattern matching is used to expand the context of the text with structured data that can also be used for ...
Despite the graph databases' advantages and recent popularity over [citation needed] relational databases, it is recommended the graph model itself should not be the sole reason to replace an existing relational database. A graph database may become relevant if there is an evidence for performance improvement by orders of magnitude and lower ...
Cypher was originally intended to be used with the graph database Neo4j, but was opened up through the openCypher project in October 2015. [ 3 ] The language was designed with the power and capability of SQL (standard query language for the relational database model ) in mind, but Cypher was based on the components and needs of a database built ...