Attendees to the recent Strata & Hadoop World conference in San Jose, CA, had a lot to say about issues related to streaming data, real-time data, and visualization challenges. But cloud-based analytics also dominated many discussions.
Nikita Ivanov, founder and chief technology officer at GridGain spoke with Information Management about why the increased willingness to host data, and data analytics, in the cloud.
Information Management: What are the most common themes that you heard among conference attendees and how do those themes align with what you expected?
Nikitaa Ivanov: I would probably point out two trends (or observations) that stood up from previous years:
First, there were visibly more people familiar with in-memory computing in general and Apache Ignite/GridGain in particular. We've seen a steady progression in this regard but this year was a breakthrough. I'd attribute that to a pivotal point that in-memory computing reached in the last 12 to 18 months as well as we dramatic growth of Apache Ignite as a project.
Second, questions about integration with and/or acceleration for Spark were much more prevalent than in the past. I believe Spark is reaching certain maturity level and as companies move from early stage evaluation to a serious production use they start facing "grown up" problems with Spark vis-a-vis performance, data storage, etc.
IM: What are the most common challenges that attendees are facing with regard to data management and data analytics?
NI: The questions that we were asked were somewhat self-selected (since we are an in-memory company and in-memory computing is all about performance and scale). The overriding challenge that we've heard over and over again was... performance and ability to process ever growing data set in a "business acceptable" timeframes.
IM: What are the most surprising things that you are hearing from attendees regarding their data management initiatives?
NI: Unequivocally, two things were surprising:
First, the move to cloud by financial services, government agencies, etc. All the previous barriers and reasons of not to go cloud are rapidly dissipating.
Second, the winding down of Hadoop MapReduce as a processing paradigm. Hand-rolled M/R jobs are clearly on the way out.
IM: What does your company view as the top data issues or challenges in 2016?
NI: Speed and scale.
IM: How do these themes and challenges relate to our company’s market strategy this year?
NI: They do relate directly. We are aiming at establishing GridGain as a leader in high-performance data processing with our In-Memory Data Fabric product.
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