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 ...

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 ...

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 ...

One question I get asked a lot by my clients is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they are ...

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 ...

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.

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 ...

If 2014 was the year that Apache Hadoop sparked the big data revolution, 2015 may be the year that Apache Spark supplants Hadoop with its superior capabilities for richer and more timely analysis.