Gigaom Hadoop Data Warehouse Interoperability Report

MapR SQL-on-Hadoop Solution Earns Highest Score in Gigaom Research Hadoop/Data Warehouse Interoperability Report


SQL is one of the most widely used languages to access, analyze, and manipulate structured data. As Hadoop gains traction within enterprise data architectures across industries, the need for SQL for both structured and loosely-structured data on Hadoop is growing rapidly. Key organizational drivers include the ability to:

- Leverage existing SQL skills in the organization
- Reuse BI, ETL, and analytics infrastructure investments with Hadoop

MapR supports SQL as a key use case along with the other types of processing on Hadoop. MapR takes an open approach to SQL, supporting the broadest set of SQL-on-Hadoop (also called "SQL-in-Hadoop") projects and technologies on the enterprise-grade MapR Converged Data Platform.

Apache Hadoop for MapR

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Broadest Support for SQL

MapR delivers maximum flexibility for SQL access in Hadoop by ensuring that its users can run the widest variety of both open-source and proprietary SQL technologies on its secure and high-performance distribution for Hadoop.

Click on the links below to learn more.

Customer Education

MapR is committed to ensuring that customers are successful with their goals for Big Data. Given the momentum in the SQL-on-Hadoop space with products from Hadoop vendors, innovative start ups, and traditional database vendors, there are many questions such as:
  • Which SQL project is best for me?
  • What are the key use cases and decision criteria?
  • How compliant with ANSI SQL and security methods are each? Does it matter?
MapR strives to be a trusted advisor to customers, providing information on the technology landscape and gathering best practices from the experts in the industry. Click below to get more information about SQL on Hadoop.