Graph databases are becoming the next big thing in data and analytics technology. According to Gartner, the application of graph processing and graph database management systems will grow at 100% ...

It's often easier to understand the use cases for graph databases than understanding how graph databases work. For instance, asking the question of who the most powerful thought leaders across ...

Every decade seems to have its database. During the 1990s, the relational database became the principal data environment, its ease of use and tabular arrangement making it a natural for the growing ...

Comcast Corp. is working on ways to better understand its customers’ families. The company plans to roll out features that enable parents to manage the devices their children use at a fine level of ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Graph databases are gaining attention as enterprises work on their next-generation artificial intelligence (AI) applications. While still a bit of an outlier, graph-oriented databases continue to find ...

The standard architecture — chunking documents, embedding them into a vector database, and retrieving top-k results via cosine similarity — is effective for unstructured semantic search. However, for ...

Twenty years ago, my development team built a natural language processing engine that scanned employment, auto, and real estate advertisements for searchable categories. I knew that we had a difficult ...

Bidding to keep its market-leading graph database engine out in front against new competition, Neo Technology Inc. today is unveiling an integration and visualization layer on top of its platform that ...

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...