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OnStrategies Perspectives



Insights on the world of Information Technology -- Views expressed here do not reflect the opinions of Ovum.



Last Build Date: Tue, 11 Oct 2016 12:12:38 +0000

 



Onwards to a Bigger Stage

Wed, 06 Jul 2016 16:12:47 +0000

For the few of you who’ve traveled the timeline, you’ll know that we’ve been blogging since well before the term entered the general vocabulary. Our very first post covered the passing of the torch from Bill Gates to Steve Ballmer at Microsoft. A couple posts later, we celebrated the fact that the Y2K bug did … Continue reading Onwards to a Bigger Stage



Hadoop and enterprise databases: Brothers from different mothers?

Tue, 12 Apr 2016 20:22:31 +0000

Hadoop has come a long way in its first decade. Doug Cutting, who along with Mike Cafarella cofounded the Hadoop project as the offshoot of the Apache Nutch web crawler (search) project, has written an elegant post from someone who wasn’t just an eyewitness, but who created history. Cutting’s main point is that the open … Continue reading Hadoop and enterprise databases: Brothers from different mothers?



Spark 2.0: Walking the tightrope

Mon, 22 Feb 2016 04:40:43 +0000

Here’s the second post summarizing our takeaways from the recent Spark Summit East. In April or May, we’ll see Spark 2.0. The direction is addressing gap filling, performance enhancement, and refactoring to nip API sprawl in the bud. Rewinding the tape, in 2015 the Spark project added new entry points beyond Resilient Distributed Datasets (RDDs). … Continue reading Spark 2.0: Walking the tightrope



Industrializing Spark

Mon, 22 Feb 2016 04:10:12 +0000

This is the first of two pieces summarizing our takeaways from the recent Spark Summit East. Given the 1000+ contributors to the Apache Spark project, it shouldn’t be surprising that development is pacing in dog years. Last year, Spark exploded as the emerging fact of life for bringing Fast Data velocity to Big Data, courtesy … Continue reading Industrializing Spark



Apache Arrow: Lining up the ducks in a row… or column

Wed, 17 Feb 2016 12:30:12 +0000

As we noted a couple years back, data is getting bigger and fast data is getting faster because of the onward declining cost of infrastructure. And nowhere has that been more apparent than with in-memory and Flash storage. For instance, when SAP HANA yanked the in-memory database from its formerly specialized niche, IBM, Oracle, and … Continue reading Apache Arrow: Lining up the ducks in a row… or column



Big Data 2015-2016: A look back and a look ahead

Wed, 09 Dec 2015 22:33:46 +0000

Quickly looking back 2015 was the year of Spark. If you follow Big Data, you’d have to be living under a rock to have missed the Spark juggernaut. The extensive use of in-memory processing has helped machine learning go mainstream, because the speed of processing enables the system to quickly detect patterns and provide actionable … Continue reading Big Data 2015-2016: A look back and a look ahead



Data Scientists are people too

Fri, 23 Oct 2015 02:02:22 +0000

There’s been lots of debate over whether the data scientist position is the sexiest job of the 21st century. Despite the Unicorn hype, spending a day with them at the Wrangle conference, an event staged by Cloudera, was a surprisingly earthy experience. It wasn’t an event chock full of algorithms, but instead, it was about … Continue reading Data Scientists are people too



Strata 2015 Post Mortem: Sparking expectations for Smart, Fast Applications

Mon, 05 Oct 2015 05:20:34 +0000

A year ago, Turing award winner Dr. Michael Stonebraker made the point that, when you try managing more than a handful of data sets, manual approaches run out of gas and the machine must come in to help. He was referring to the task of cataloging data sets in the context of capabilities performed by … Continue reading Strata 2015 Post Mortem: Sparking expectations for Smart, Fast Applications



So is Spark really outgrowing Hadoop?

Mon, 28 Sep 2015 02:27:24 +0000

That’s one of the headlines of a newly released Databricks survey that you should definitely check out. Because Spark only requires a JVM to run, there’s been plenty of debate on whether you really need to run it on Hadoop, or whether Spark will displace it altogether. Technically, the answer is no. To run Spark, … Continue reading So is Spark really outgrowing Hadoop?



Hadoop and Spark: A Tale of two Cities

Tue, 16 Jun 2015 06:24:50 +0000

If it seems like we’ve been down this path before, well, maybe we have. June has been a month of juxtapositions, back and forth to the west coast for Hadoop and Spark Summits. The mood from last week to this has been quite contrasting. Spark Summit has the kind of canned heat that Hadoop conferences … Continue reading Hadoop and Spark: A Tale of two Cities