Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

Big Data, that is data which pushes the limits of conventional data management technology, is difficult or impossible to manage with relational databases. In fact, that’s pretty much the ...

On current trends, then, we can expect NoSQL and relational databases to share the big data winner’s podium for many years to come. NoSQL rising.

NoSQL database technologies (key/value, wide column, document store, and graph) are currently very common in big data and analytics projects. But these products are not designed to be wholesale ...

As for new types of data, relational database products evolved to support unstructured data back in the 1990s, he said. In 2013, Oracle’s namesake database added support for JSON (JavaScript ...

Even with all the hype around NoSQL, traditional relational databases still make sense for enterprise applications. ... In 2010, the talk about a "big data" trend has reached a fever pitch.

Quite a good idea for big data. In relational databases you define your schema BEFORE you add your data. So a database with name, address, phone number etc. has those core defined schemas shapes.

Companies who are adopting the graph approach are fundamentally transforming their organizations in the “data age.” Semantic graph databases are the successors of relational databases. They represent ...

Microsoft, IBM, Oracle: Three vendors, three different paths on dealing with the Hadoop open-source data processing technology Topics Spotlight: Prioritizing your AI investments ...

Relational databases are built on a model that uses a structure of tables linked by defined relationships expressing dependencies between the data. Primarily, relational databases are used for ...