6 retrieval augmented generation (RAG) techniques you should know

Graph Databases Databases Big Data

Weaviate Landing Page

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Weaviate

Welcome to Weaviate

The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill.

#Utilities #Application Utilities #Search Engine 37 social mentions
neo4j Landing Page
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neo4j

Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
Pricing:
- Open Source
The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill.

#Graph Databases #Big Data #Databases 34 social mentions
Amazon Neptune Landing Page

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Amazon Neptune

Amazon Neptune is a fully managed graph database service that works with highly connected datasets. Learn about the benefits and popular use cases.

The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill.

#Graph Databases #Databases #NoSQL Databases 11 social mentions