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 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.

He explained that the new service helps customers analyze existing Neptune graph data or data lakes on top of S3 storage, taking advantage of vector search to find key insights.

TigerGraph, the enterprise AI infrastructure and graph database leader, is releasing its next generation graph and vector hybrid search, delivering the industry's “most advanced” solution for ...