Gartner Research

What Apache Spark Means for Big Data

Published: 25 February 2015

ID: G00271327

Analyst(s): Nick Heudecker


With its fast, in-memory processing and analytical framework, Apache Spark has quickly attracted interest from developers and software vendors. Information managers and business analytics leaders must weigh Spark's benefits against its relative immaturity and incomplete vendor support story.

Table Of Contents
  • Impacts


Impacts and Recommendations

  • Apache Spark's memory-centric data-processing framework enhances batch, streaming and machine-learning tasks, but information managers and business analytics leaders must also factor in its uneven levels of maturity
  • Commercial support for Spark is almost always bundled with other data management products, but information managers and business analytics leaders must be aware that Spark's development pace makes it challenging for bundling vendors to constantly support the latest component versions

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