If you want to know what’s what in Big Data analytics today, you’ve got to know the basics of NoSQL databases, and how appropriate NoSQL databases facilitate Big Data analytics. What are the most ...

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 ...

NoSQL operational databases are rapidly gaining adoption. They’re easier to use, operate, and scale than their relational counterparts, and they enable faster development of richer applications.

MapR Technologies Inc., known as one of the top commercial vendors distributing Big Data software based on Apache Hadoop technology, today added JSON support to its MapR-DB NoSQL database, claiming ...

Even though MongoDB and Cassandra keep winning converts, enterprises are keeping their RDBMSes around, and will do so for quite some time. NoSQL promised to upend the database market as big data ...

NoSQL databases manage large volumes of data in systems such as Web applications. The future, though, could see NoSQL systems fitted for real-time analytics,as well as being part of a consolidation of ...

This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics. What is a graph database? Graph databases organize facts into connected bundles, ...

Objectivity, Inc. and Database Trends and Applications will present a webcast on the latest trends in big data analytics on Thursday April 12 at 9 am PT/ 12 noon ET. The webcast will cover the ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Andy Brinkmeyer shares how engineering ...

With low-code/no-code tools revamping enterprise app development, analytics firm SlamData Inc. has come out with a release of its namesake platform claiming to provide "no-code BI for NoSQL." The ...

It’s commonly asserted—and generally accepted—that the era of the “one-size-fits-all” database is over. We expect that enterprises will use a combination of database technologies to meet the distinct ...