When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more ...

With AI at the data level, you can use that model to do a lot of the work, and then apply vector search on top of that.

Part 2 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the database system space including Cockroach Labs, MongoDB, MariaDB and Redis Labs.

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

Increasingly, customers are demanding that their databases take on multiple chores. Emergence of multi-model databases providing developers multiple paths through APIs is the latest evidence of ...

One of the most important steps in desiging a database is establishing the data model. Part one of a two-part article describes how to create a logical model.

On the morning of August 21, Dameng Data's Vice General Manager, Fu Xin, delivered a keynote speech titled "Intelligent Multi ...

ArangoDB: Suitable for startups and SMBs, ArangoDB is a multi-model database that supports graph, document, and key/value data models.

In a graph database, every element contains a direct pointer to its adjacent element and no index lookups are necessary. Before looking into a graph database provider, make sure your intended use ...

This approach features a centralized database linked to other data stores with a common data model that carries information from one point to another, without the need to rewrite code.