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Categories: Amazon Apache Hadoop Spark

Companies are quickly ramping up their investments fast data analytics and real-time stream processing frameworks and lowering spending on batch technologies in an attempt to get on top of growing data volumes and velocities, a new survey says. According to OpsClarity‘s 2016 State of Fast Data & Streaming Applications Survey, 89 percent of more than 4,000 survey respondents say they’re currently using batch analytics, compared to 65 percent who say they’re using “near real-time pipelines.” Looking forward, 92 percent of survey respondents indicate they plan on increasing their investments in streaming data applications over the next year, while nearly 79 percent say they planned on reducing or eliminating investments in batch processing. Those numbers, more than any others in the survey, demonstrate the shift that’s occurring in the big data analytics space, as companies look to take advantage of surging data flows to create a competitive advantage for themselves. “Real-time data and stream processing is becoming central to how a modern company harnesses data,” Apache Kafka creator Jay Kreps says in a statement that accompanied the release of the survey. “For modern companies, data is no longer just powering stale daily reports. It’s being baked into an increasingly sophisticated set of applications, from detecting fraud to powering real-time analytics, to guiding smarter customer interactions.”

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