Big Data Analytics Platform

Ultra-fast, high concurrency SQL for Hadoop and
data warehousing

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Transform Hadoop into your best platform for BI

Allow your business users to interactively query big data using their preferred BI tools

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Inmar puts Kognitio at the heart of its retail analytics portal

Kognitio’s high-speed processing means Inmar can offer more and more real-time queries through its customer portal, allowing them to offer very detailed targeting that otherwise wouldn’t be possible.

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Why choose Kognitio

By running Kognitio’s SQL engine on your big data, you’ll get ultra-fast query results for thousands of concurrent users.

 

Fastest SQL on Hadoop

Ultra-fast SQL for huge working sets in either Hadoop or your traditional data warehouse. Kognitio beats Impala, Hive LLAP, Presto and Spark SQL.

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Thousands of complex queries per second

Unrivalled throughput meaning you can serve answers to thousands of concurrent users throughout your business.

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Real-world SQL, tuned for BI queries

Kognitio runs ANSI standard SQL queries. Whether the queries are hand-written or generated by your BI tool, Kognitio slots into your existing workflow.

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Tableau with 9 petabytes in Hadoop

The world’s largest card provider serves business insight to enterprise customers globally with Kognitio.

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Resilient, highly performant in-memory analytics

bet365 gets deeper insight at speed with Kognitio.

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Real-time point of sale analysis at AIMIA

AIMIA uses Kognitio to help retailers and suppliers understand consumer behavior.

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I’ve put data in Hadoop so analytics will be quick, right?

Catherine Nottage | Jun 11, 2018

Volume, variety and velocity are the three known defining properties that put the ‘big’ in ‘big data’. Hadoop helps businesses overcome many of the challenges of dealing with these three properties, but does it solve all of them? Does velocity mean faster analysis? While data is constantly collected from hundreds of sources at speed does…

Enhancing MPP performance with intelligent parallelism

Mark Chopping | May 18, 2018

Companies have long accepted that with the explosion in data volumes described in this Analytics Week article. this Inside Big Data article  and elsewhere, that Massively Parallel Processing (MPP) is the only way to deal with today’s data processing requirements. This Microsoft tech blog post outlines the reasons for moving to MPP for data processing. MPP systems…

How BMW uses big data to boost maintenance and customer service

Catherine Nottage | May 11, 2018

With big data analytics now becoming a fixture across companies of all sizes and every industry, many businesses will be looking at how they can leverage the technology to gain a march on their competitors and provide the highest possible level of service. After the EMC World Conference in 2015, we read with interest about…

Big data sets – where to find and how to harvest them

Chak Leung | May 04, 2018

Finding big data sets to work with isn’t easy. People who’d like to share need to be wary of the sensitivity of the data they’re sharing (e.g. social media data is very personal) and generally a lot of interesting data sets are off limits because of this. I’ve detailed in this blog some repositories for…