Amazon said through the new model, 4DBInfer, the company aim to accelerate research on graph-centric predictive modeling for relational databases by providing a unified, fully open-sourced framework.

At a time when every enterprise looks to leverage generative artificial intelligence, data sites are turning their attention to graph databases and knowledge graphs. The global graph database market ...

Data models are used to represent real-world entities, but often have limitations. Avoid common data modeling mistakes for data integrity.

SqlDBM today announced that it has been selected as winner of the “Database Modeling Solution of the Year” award in the 4th annual Data Breakthrough A ...

However, with the intensifying competition, enterprises face numerous challenges when selecting a vector database. Issues such as inadequate performance, low throughput, high latency, lack of ...

Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

The process of de-identifying test databases can be approached in a variety of ways, and we’re often asked how our approach differs as compared to others. In this article, we’ll explore how our ...

“SqlDBM is an online database modeling tool and very much in the ethos of Snowflake,” he noted. “What Snowflake is to databases, SqlDBM is to modeling.

Google Cloud recently added support for the pgvector on Cloud SQL for PostgreSQL and AlloyDB for PostgreSQL. The extension brings vector search operations to the managed databases, allowing ...

Enterprises are creating huge amounts of data and it is being generated, stored, accessed, and analyzed everywhere – in core datacenters, in the cloud distributed among various providers, at the edge, ...