Sometimes a logical data model is referred to as asemantic data model. A semantic data model focuses on the content and context of the data. All components of the data model are translated into business-friendly
The semantic data model is a method of structuring data in order to represent it in a specific logical way. It is a conceptual data model that includes semantic information that adds a basic meaning to the data and the relationships that lie between them. This approach to data modeling and ...
What Does Data Model Mean? A data model refers to the logical inter-relationships and data flow between different data elements involved in the information world. It also documents the way data is stored and retrieved. Data models facilitate communication business and technical development by ...
A common data model standardizes the logical infrastructure of software systems so that many related applications can operate on and share the same data.
Entity-relationship model Document model Entity-attribute-value model Star schema The object-relational model, which combines the two that make up its name You may choose to describe a database with any one of these depending on several factors. The biggest factor is whether the database manageme...
Use Cases: RDF graph databases are useful in applications like knowledge graphs, ontologies, and semantic web projects. How Does a Graph Database Work? Below is a detailed overview of how graph databases work: Data Model: Nodes: Nodes represent entities or data points in the database. Each ...
What is Similarity Search in Vector Databases? Similarity search, also known as vector search, vector similarity, or semantic search, refers to the process when an AI application efficiently retrieves vectors from the database that are semantically similar to a given query’s vector embeddings ...
A graph database, also referred to as a semantic database, is a software application designed to store, query and modify network graphs. A network graph is a visual construct that consists of nodes and edges. Each node represents an entity, such as a person, and each edge represents a co...
The database is distributed under the open source BSD-3-Clause license. Its strength is approximate nearest neighbors (ANN) searches, whose results enhance generative AI queries. Customers can run Weaviate on their own computers, in a public cloud service in a serverless model, or through the ...
This is why vector databases are so important. They simplify fundamental operations for generative AI apps by storing large volumes of data in the structure that generative AI applications need for optimized operations. Optimized Semantic Search:Generative AI applications rely on data representations of ...