Today’s “big data stack” includes databases, data management software and data analytics tools – all critical components of an effective operational or analytical data system. But all those ...

One of the major barriers to any successful Big Data project is mastering all of the technologies needed to make it happen. Big Data has evolved into a mish-mash of technologies, with Hadoop at the ...

Back in the early 1990s, you would sometimes hear this gag: “Two major products that came out of Berkeley: LSD and UNIX. We don’t believe this to be a coincidence.” Although wildly inaccurate, this ...

Input from theCUBE and data practitioner communities suggests that acceleration in compute performance and the sophistication of the modern data stack is outpacing the needs of many traditional ...

A data-processing solution from Mesosphere leverages Spark, Kafka, and Cassandra -- but eschews Hadoop -- for enterprise level real-time big-data needs Mention big-data tools like Spark and Kafka to ...

SANTA CLARA, Calif.--(BUSINESS WIRE)--Accelerite, a provider of infrastructure software for digital transformation, today announced ShareInsights 2.0, an end-to-end, self-service big data analytics ...

Though a bit late, Google finally joined the bandwagon by launching a new service called Cloud Dataproc for processing Big Data and analytics. The platform supports real-time streaming, batch ...

Big data systems tend to be large, complex and often hard to troubleshoot. In the world of databases, web and mobile stacks, application performance management services like AppDynamics and New Relic ...

SAN FRANCISCO — Hospitals need to move from a lagging reactive traditional business intelligence and statistics stance into a leading proactive analytics approach. Put another way: It’s time for the ...

Today’s “big data stack” includes databases, data management software and data analytics tools – all critical components of an effective operational or analytical data system. But all those ...