by Angela Guess
Ken Hess recently wrote in ZDnet, “In a new survey conducted by Syncsort, 250 prominent respondents including data architects, IT managers, developers, business intelligence/data analysts, and data scientists weigh in on big data trends to watch in 2016. Two-thirds of those surveyed work in companies with over $100 million in annual revenue. Industries represented are financial services, healthcare, government, and retail. The big trend for 2016 is the move away from Hadoop experimentation into full production with big data analytics. 2016’s big three trends are: (1) Apache Spark production deployments. (2) Conversion from other platforms to Hadoop. (3) Leveraging Hadoop for advanced use cases.”
Hess goes on, “The uptick in Apache Spark is a bit of a surprise at a full 70 percent of respondents stating that Spark is the platform that they’re most interested in. MapReduce came in at a distant second at 55 percent. However, Syncsort’s big data analysts predict that MapReduce will remain the primary compute framework for production deployments. But the numbers tell a different story. With 70 percent of the respondents expressing a keen interest in Apache Spark, MapReduce deployments may in fact reduce over the next twelve months. The two primary factors in this interest in Spark is that it is easy to deploy and its speed. Because Spark runs in memory, it requires big iron. Its speed also highlights one of MapReduce’s biggest problems: its high-latency, batch-mode response.”
photo credit: Hadoop