As analytics accelerate closer to real-time, historical analytics are not being displaced. The benefits of a comprehensive and historic view of data is becoming more than just a daydream. Imagine a ...

The in-memory batch-processing framework sheds more JVM performance bottlenecks as a major Hadoop vendor eyes Spark as a full-blown replacement for the aging MapReduce Apache Spark, the in-memory data ...

Apache Spark is an execution engine that broadens the type of computing workloads Hadoop can handle, while also tuning the performance of the big data framework. Hadoop specialist Cloudera recently ...

Apache Spark, the in-memory and real-time data processing framework for Hadoop, turned heads and opened eyes after version 1.0 debuted. The feature changes in 1.2 show Spark working not only to ...

While MapReduce still enjoys widespread use in the Hadoop ecosystem, the number of new deployments that are being brought online is declining. And the trend has not gone unnoticed by the vendors that ...

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 ...

There is more to big data than Hadoop, but the trend is hard to imagine without it. Its distributed file system (HDFS) is helping businesses to store unstructured data in vast volumes at speed, on ...

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 ...