A Vector DB stores and manages unstructured data — text, images, audio, etc. — as vector embeddings (numerical format). These embeddings capture the semantic relationships between the data points.

With the existing capabilities of Neoj4, Eifrem said that the graph database captures explicit relationships between concepts. What vectors do is draw out implicit relationships in data.

One of the best-known graph databases is Neo4j, which recently announced support for the enterprise version of its cloud-hosted service, Aura, on Azure.Available in the Azure Marketplace, it’s a ...

An essential component for building more trustworthy AI lies in creating a more solid data foundation on top of graph databases, knowledge graphs, and vector databases. Each element plays a ...

Despite these reasons, organizations implement graph databases when the data exhibits the characteristics described above, or the data volumes, regardless of data structure, are billions of rows.

A graph database is a type of data model structured to help users better understand relationships between different data points and content. There are multiple graph databases in the market today ...

The intersection of large language models and graph databases is one that’s rich with possibilities. The folks at property graph database maker Neo4j today took a first step in realizing those ...

The vector database cloud service may attract developers with performance and cost advantages over traditional databases for AI-related workloads, analysts say. San Francisco-based Zilliz has ...

These include updates to its Spanner SQL database, which now features graph and vector search support, as well as extended full-text search capabilities. This wouldn’t be a Google announcement ...

TigerGraph Inc. is upgrading its graph database with a hybrid search capability designed to power artificial intelligence applications.The Redwood City, California-based startup debuted the featu ...