Listen in on any conversation about big data, and you’ll probably hear mention of Hadoop or Apache Spark. Here’s a brief look at what they do and how they compare. 1: They do different things. Hadoop ...

June was an exciting month for Apache Spark. At Hadoop Summit San Jose, it was a frequent topic of conversation, as well as the subject of many session presentations. On June 15, IBM announced plans ...

Just when Hadoop was getting settled, the open-source world is already ready to kill it. Not all of it, mind you. But MapReduce, that genius insight from Google that developer Doug Cutting turned into ...

There’s been a lot of rhetoric around Apache Spark over the last few years. Back in the fall of 2014, some even suggested — only partly in jest — that the Hadoop World conference change its name to ...

This guest post comes courtesy of Tony Baer's OnStrategies blog. Baer is a principal analyst covering Big Data at Ovum. If it seems like we've been down this path before, well, maybe we have. June has ...

Once, Hadoop and MapReduce were nearly synonymous, but today, Spark is the framework of choice for a new wave of big data practitioners Hadoop has never been in more desperate need of a lift than now.

Apache Spark and Apache Hadoop are both popular, open-source data science tools offered by the Apache Software Foundation. Developed and supported by the community, they continue to grow in popularity ...

Apache Spark has become the de facto standard for processing data at scale, whether for querying large datasets, training machine learning models to predict future trends, or processing streaming data ...

The popular Apache Spark project is poised to break from the Hadoop ecosystem as an independent data processing tool, and it may shift from on-premises installations to the cloud, according to new ...

The first Spark Summit East conference concluded yesterday, just a month after Apache Spark practically stole the show at the Strata+Hadoop World conference, reinvigorating the debate about where the ...