2014 was my first full calendar year working for Gartner. Between events and travel, I kept busy collaborating on a variety of research.
In Choosing Your SQL Access Strategy for Hadoop, Merv Adrian and I explored the different approaches vendors are taking with SQL and Hadoop. This was a hot topic in the vendor space throughout 2014, but clients weren’t as interested. Enterprises either assume some form of SQL access will be available for Hadoop or their preexisting tools support it. I expect we’ll hear more about this topic in 2015, but SQL on Hadoop should be considered table stakes by now.
A Tour of NoSQL in Eight Use Cases was another collaboration with Merv (that will be a recurring theme). This note looked at a handful of different use cases for NoSQL DBMSs, breaking them up by their respective types (document, table style, graph and key-value). Figuring out how to apply new technologies is challenging and this note really resonated with our readers. We hope to follow it up with a similar note on Hadoop use cases in 2015.
Just because a vendor doesn’t qualify for a Magic Quadrant doesn’t mean there aren’t some cool technologies and business models out there. That’s where the Cool Vendors notes come it. Cool Vendors in DBMS, 2014 presented Neo Technologies, Splice Machine, Sqrrl and Tokutek. We’ve already started collecting ideas for 2015.
Harnessing Big Data Velocity With Stream Processing was a chance to collaborate with Roy Schulte on the impacts of high velocity data. I expect this topic to gather more steam in 2015 as enterprises grapple with data in motion.
The Data Lake Fallacy: All Water and Little Substance, with Andrew White, got quite a bit of attention. We saw this term emerging in the information management space and felt we to get in front of it. Data lakes have their uses, but enterprise-wide data management isn’t one of them. We plan on publishing a best practices note in 2015.
The Market Guide for NoSQL DBMSs was a follow-up to 2013’s Who’s Who in NoSQL DBMSs. With traditional vendors embracing many of the distinctions of NoSQL vendors, the term is becoming less meaningful, and therefore less important. But other factors, such as multi-model DBMSs, are starting to influence the space. I’m already looking forward to the 2015 update to this note.
In Survey Analysis: Big Data Investment Grows but Deployments Remain Scarce in 2014, Lisa Kart and I revisited our 2013 big data adoption survey. We saw a 10% increase in the number of organizations reporting big data investment, but a less substantial increase in deployments. I believe this indicates how challenging big data is for most enterprises. Lisa and I hope to revisit this survey again in 2015.
The first note I published when I joined Gartner, Applying the Big Data Ecosystem, was translated to Chinese: China Summary Translation: Applying the Big Data Ecosystem. I had nothing to do with the translation, but thought it was cool enough to mention.
Finally, the Gartner year typically closes with predictions. I got to lead our big data predictions effort – which entails sending just enough email to get a response without getting banished to the spam folder. The predictions for Predicts 2015: Big Data Challenges Move From Technology to the Organization all indicated one thing: the technology side of big data won’t be where future challenges reside. Emerging tech is maturing (more or less) and traditional vendors are revamping their offerings to cope with emerging information challenges. The question is whether organizations will mature in kind.
So that’s my year. It seemed busier when it was happening. My research agenda for the first half of 2015 is taking shape and it promises to be another interesting twelve months.
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