Graph databases represent one of the fastest-growing areas in the database market. MarketsandMarkets’ report on graph databases predicts that graph databases will grow from $1.9 billion in 2021 to ...
Over the past decade, we’ve seen a wave of diversification followed by consolidation in database technologies. Relational databases such as Oracle, MySQL, and SQL Server completely dominated ...
GA release accelerates production streaming pipelines with real-time CRUD synchronization, reusable data flows, ...
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 ...
Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
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 ...
SurrealDB 3.0 launches with $23M in new funding and a pitch to replace multi-database RAG stacks with a single engine that handles vectors, graphs, and agent memory transactionally.
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 ...
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