Big Data

Hadoop and MapR

When the Vertica Analytics Platform and MapR pair together, you don’t just receive the highest-grade enterprise capabilities, you receive a tightly integrated best-of-breed solution for SQL-on-Hadoop that is fully compliant with ANSI SQL and Linux standards. Vertica and MapR give you a transformational data infrastructure to very quickly and easily explore big data volumes. Grow and exploit business intelligence in virtually any way you dream possible.


  • The Vertica Analytics Platform and Hadoop are highly complementary systems for big data analytics.
  • The Vertica Analytics Platform is ideal for interactive, blazing-fast analytics and Hadoop is well suited for batch-oriented data processing and low-cost data storage. When used together, with tight integration and support for all Hadoop distributions, the Vertica Analytics Platform and Hadoop offer the most open SQL on Hadoop.
  • The organizations can use the most powerful set of data analytics capabilities and do far more than either platform could do on its own, extracting significantly higher levels of value from massive amounts of structured, unstructured, and semi-structured data.


  • Vertica operates directly in MapR Distribution for Hadoop 100% ANSI SQL compliant
  • Support for a mixed variety of data structures
  • Native redundancy, high availability, and disaster recovery
  • Rich set of built-in analytic functions
  • Apache Hadoop projects Mahout, Hive, Pig, and more
  • Fast schema-less exploration with HP Vertica Flex Zone
  • Automated Vertica analytic database design tools
  • Strong data security and management

Benefit / Value

  • Access and interactively analyze a wider variety of data types at scale
  • Quickly ingest data without separate cluster
  • Leverage existing SQL skills, BI tools, and programming expertise
  • Perform advanced analytics faster and deeper directly on data in Hadoop
  • Lower administration across both environments (Hadoop and HP Vertica Analytics Platform)
  • Implement end-to-end data