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.
In this blog, Kognitio's VP Analytics & Consulting, Sharon Kirkham, reviews the pitfalls of benchmarking SQL on Hadoop.
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.
As part of our ongoing SQL on Hadoop platform testing, we looked at Presto. Here you can read about our initial findings.
In this blog you can read about how Hive LLAP performed against Kognitio in benchmark tests that used 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.
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?
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.
In this Market Report, Bloor Research explores the need for SQL on Hadoop and reviews the most suitable SQL engine for different use cases.
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.
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.
Want to make Hadoop your best BI platform? Read our guide on getting fast answers to big questions.
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.
In this video we demonstrate interactive querying of data in Hadoop using Kognitio as the SQL engine and Tableau as the interactive BI tool.