Cloud computing and the use of appliances will drive the next wave of big data adoption to less technically sophisticated, more mainstream enterprise audiences as investment in big data remains high this year, according to Ovum’s 2016 Trends to Watch: Big Data report.
The new report from this global research and advisory firm predicts that although Spark is poised to become the fastest growing set of analytic workloads, SQL will continue to dominate big data.
“Don’t count SQL out,” said report author Tony Baer, principal analyst, Ovum. “SQL-on-Hadoop remains a potent draw for Hadoop vendors who are aiming to reach the large base of enterprise SQL developers out there.”
However, newer kid on the block, Spark is on a definite growth spurt.
“Spark will be complementary to SQL by providing additional paths to insights, such as through the streaming of graph analysis, which can then be queried using language that enterprise database developers are very familiar with,” said Baer.
Ovum forecasts that the most significant aspect of Spark’s growth will be for third-party analytic tools’ ecosystems that embed Spark computing, stating that Spark’s machine learning capability will become “a checklist item” for data preparation and predictive analytics.
The report also predicts that data lake adoption will heat up and become a “front-burner issue” for mature Hadoop adopters, resulting in increased demand for governance tools. Look for significant growth in tools that build on emerging data lineage capabilities to catalogue, protect, govern access, tier storage and manage the lifecycle of data stored in data lakes.
“Governance of data lakes will not be built in a day. While some of the tooling exists today, capabilities such as managing the lifecycle of multi-tiered storage will have to be extended to cover the growing heterogeneity of Hadoop clusters,” said Baer.