Category Archives: SQL-on-Hadoop

Modern Data Architecture Podcast

Great news! I have participated in a podcast recorded by Pivotal and published in our official blog. In this podcast I discuss the data architecture in general – how the things started, what was the main driver for its evolution and what we have now as a “modern data architecture”. Come and listen here: http://blog.pivotal.io/pivotal-perspectives/features/discussing-modern-data-architecture

Pivotal Podcast Modern Data Architecture

Text transcript of this talk is also available by the same URL

Hadoop vs MPP

Over the latest time I’ve heard many discussions on this topic. Also this is a very popular question asked by the customers with not much experience in the field of “big data”. In fact, I dislike this buzzword for ambiguity, but this is what the customers are usually coming to us with, so I got to use it.

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If we take a look 5 years back, that was the time when Hadoop was not an option for most of the companies, especially for the enterprises that ask for stable and mature platforms. At that very moment the choice was very simple: when your analytical database grow beyond 5-7 terabytes in size you just initiate an MPP migration project and move to one of the proven enterprise MPP solutions. No one heard about the “unstructured” data – if you got to analyze logs just parse them with Perl/Python/Java/C++ and load into you analytical DBMS. And no one heard about high velocity data – simply use traditional OLTP RDBMS for frequent updates and chunk them for insertion into the analytical DWH.

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Splice Machine

Today I will tell you about the startup called “Splice Machine”. They position themselves as “The Only Hadoop RDBMS”, which is quite bold given the boom we see now in SQL-on-Hadoop solutions field, almost each of the big vendors implemented their own “one and only” solution and claim it to be the best. But let’s take a look at its internals to say whether its design really reflects the marketing slogan they’ve chosen.
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