Get in on the widespread excitement over Apache Spark. Check out the highlights from a recent SparkInsight CrowdChat that tackled six key questions about this next-generation, cluster-computing, runtime processing environment and development framework for in-memory processing of advanced analytics.
An increasing number of use cases for big data and analytics can be Apache Spark's sweet spots. Take a look at several low-latency applications in which Spark is well-suited for analysis of cached, live data.
Data scientists combine quantitative and statistical modeling expertise with business acumen and a talent for finding hidden patterns. IBM BigInsights 4.0 helps them accelerate data-science initiatives through support for Apache Spark 1.2.1, which can deliver dramatic performance improvements.
The drive toward industry openness continues at full speed, and Apache Spark is expected to become one of the centerpieces of the big data industry fabric. As a closely aligned technology with Apache Hadoop, it stands to benefit from broad adoption of core open data platform technologies.
As part of IBM's ongoing commitment to Hadoop and the broader open source ecosystem, IBM is joining forces with Databricks, Cloudera, Intel and MapR to broaden support for Apache Spark. IBM's goal is to provide enterprise customers with access to the latest innovations around big data and analytics.