MemSQL, VoltDB Vie For In-Memory Big Data Role - InformationWeek

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2/12/2015
11:46 AM
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MemSQL, VoltDB Vie For In-Memory Big Data Role

MemSQL, VoltDB present in-memory databases as alternatives to a menagerie of "science projects" used in real-time big data apps. Is SQL simpler?
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VoltDB expects to displace Spark Streaming, Storm, and other tools.
VoltDB expects to displace Spark Streaming, Storm, and other tools.

2 of 2
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D. Henschen
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D. Henschen,
User Rank: Author
2/12/2015 | 2:30:25 PM
Correction: VoltDB says it can replace Spark Streaming, not the entire Spark framework
I've tweaked this article to say that VoltDB specifically presents itself as an alternative to Spark Streaming (as you'll note if you follow the link I provided in the story), not the entire Apache Spark framework (the article originally said just "Spark"), which addresses multiple types of data analysis. It also says it can be complementary to Spark, but if you're rejecting Spark Streaming for use in a streaming app that you're choosing VoltDB to support, I'm not quite sure what's left for Spark to handle. I've asked the folks at VoltDB to add a comment on that nuance, so hopefully you'll see more on that here.
ryanbetts
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ryanbetts,
User Rank: Apprentice
2/12/2015 | 5:12:21 PM
Re: Correction: VoltDB says it can replace Spark Streaming, not the entire Spark framework
Thank you Doug.


VoltDB competes with Spark streaming - especially in cases where spark streaming is used to sessionize, transform incoming streams or implement real time analytics (in the style of a Lambda speed layer).

However, VoltDB integrates with a breadth of OLAP and Hadoop tooling - including Spark. In these cases, developers use Spark to calculate OLAP style analytics against large data sets and use those outputs in VoltDB to build real time applications for personalization, fraud alerting, and streaming analytics.

For example, one VoltDB user deploys VoltDB in combination with Spark to detect online advertising bot fraud. VoltDB is performing a sessionization function - processing 100,000's of events per second into sessions -  while Spark is used to run machine learning algorithms that detect fraud. 
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