Big data is no longer a war between batch and streaming data processing. It's not either/or, but rather a matter of "and."
Enterprises increasingly need to integrate batch and streaming data processing within a common framework, from runtime to analytics. And yet, with the rise of streaming analytics, integrating streaming data into batch-based systems is non-trivial.
Getting data from disparate data stores and running analytics on them in real-time is a huge technological challenge. While there are two primary approaches to cracking this data federation problem today, a third has emerged that just might offer the most promise.
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