Actian Blog / Tag / Hadoop Analytics

Tagged Posts: Hadoop Analytics

Accelerating Spark With Actian Vector In Hadoop
  • May 9, 2016

Accelerating Spark with Actian Vector in Hadoop

One of the hottest projects in the Apache Hadoop community is Spark, and we at Actian are pleased to announce a Spark-Vector connector for the Actian Vector in Hadoop platform (VectorH) that links the two together. VectorH provides the fastest and most complete SQL in Hadoop solution, and connecting to Spark opens up interfaces…

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Pssst .. Have You Heard About VectorH?
  • May 4, 2016

Pssst .. Have you heard about VectorH?

Hello World! We’ve been busy building some innovative features into the Actian Vector in Hadoop (VectorH) product and we would love to tell you all about them. So, the list of the features and innovations that we have done recently for VectorH… wait .. do you even know what VectorH is about? Yes, it’s…

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  • May 3, 2016

Amazon EMR as an Easy-to-set-up Hadoop Platform

Recently I helped a customer perform an evaluation of Actian Vector in Hadoop (VectorH) to see if it could maintain “a few seconds” performance as the data sizes grew from one to tens of billions of rows (which it did, but that’s not the subject of this entry). The customer in question was only…

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Taking Advantage Of Ordered Data
  • May 2, 2016

Taking Advantage of Ordered Data

Actian Vector and Vector in Hadoop (VectorH) have a lightweight, but very potent, feature that can give a significant performance boost when querying data that possesses some kind of ordering. This entry takes a look at this feature and describes how to use it. The feature utilises what are referred to as MinMax structures.…

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Hadoop At 10
  • April 27, 2016

Hadoop at 10

Wow – 10 years of Hadoop, what a ride. Actian has been working in the Hadoop ecosystem almost since the beginning, starting in 2007. Actian started working with Hortonworks the moment they launched in 2011. As a pioneer in this space, we have witnessed the whole “boom”. And while Hadoop is continuing to show…

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Analytics Cube And Beyond
  • April 14, 2016

Analytics Cube and Beyond

Big Data engineering has invented a seemingly endless supply of workaround solutions.  These are for both scalability and performance problems.  Ultimately, our approach to solving these problems dictates how sustainable they will be.  This post compares some modern best practices with pre-processing cube environments.  3 Ways A Hadoop Database Competes With Cube Analytics Software…

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