SQL on Hadoop - Kognitio

A major hindrance to the success of Hadoop projects has been the inability for wider business users to query data in Hadoop in the ways they have been used to i.e. using analytics tools like Tableau. Queries written with data analytics tools typically generate SQL, but Hadoop data is stored in a non-structured manner which makes it very difficult for most BI tools to return query results in a timely manner, and for a large number of business users at the same time!

This is where SQL on Hadoop comes in. Here we share some of our articles, comparisons and recommendations for SQL on Hadoop.

SQL on Hadoop benchmarking

All I want is an "honest" benchmark

In this blog, Kognitio's VP Analytics & Consulting, Sharon Kirkham, reviews the pitfalls of benchmarking SQL on Hadoop.

How do the different SQL on Hadoop tools fare in the 99 TPC-DS test queries?

Over the past year, we've been testing different open source SQL on Hadoop solutions. Read this blog for a summary of all of the results.

Presto performance benchmarks

As part of our ongoing SQL on Hadoop platform testing, we looked at Presto. Here you can read about our initial findings.

Hive LLAP and Kognitio benchmarking using TPC-DS query set

In this blog you can read about how Hive LLAP performed against Kognitio in benchmark tests that used the TPC-DS query set.

Apache Impala and SparkSQL benchmark tests using the TPC-DS query set

This testing conducted in March 2017, evaluates the performance of Apache Impala and Apache Spark alongside Kognitio's analytical platform. Read the results in this blog.

Why SQL on Hadoop is one option for gaining real ROI from big data

ROI for Hadoop is difficult to quantify. With a shortage of data science talent to analyze big data, how does a business widen the scope for analysis of Hadoop-based data?

Four ways to get it wrong with SQL on Hadoop

More than half of professional developers work with SQL. Despite its imperfections, SQL is how the world queries data. Businesses apply SQL to Hadoop-based data to make querying the data easier but here are four of the ways that SQL on Hadoop projects tend to get it wrong.

Bloor Research Market Report: SQL engines on Hadoop

In this Market Report, Bloor Research explores the need for SQL on Hadoop and reviews the most suitable SQL engine for different use cases.

BI & Analytics on Hadoop

Seven reasons why we need SQL now more than ever

In this blog, Kognitio COO outlines seven reasons why he believes we need SQL now more than ever, including its ease of use and supporting tools.

BI on Hadoop is possible, if you select the right SQL technology

Ever tried connecting BI tools like Tableau to Hadoop? If you believe it can't be done, then read this blog where Kognitio CEO Roger Gaskell outlines things you should consider when selecting a SQL interface to your Hadoop cluster.

Transform Hadoop into your best BI platform

Want to make Hadoop your best BI platform? Read our guide on getting fast answers to big questions.

Enterprise level, high-concurrency BI on Hadoop is possible

Enterprise Level BI is not simply about supporting complex SQL syntax. It is about supporting the needs of 100s of end users all with different needs. So a mixed workload and concurrency. In this video we prove that enterprise-level BI on Hadoop is possible - using 5.2billion rows of Transport for London (TfL) data as an example.

Analyzing Transport for London data using Kognitio and Tableau

In this video we demonstrate interactive querying of data in Hadoop using Kognitio as the SQL engine and Tableau as the interactive BI tool.