Data, Analytics & Technology

Solve complex queries and Big Data challenges

As a leading information provider, LexisNexis has more than 40 years experience in managing big data, from publicly available information such as worldwide newspapers, magazines, articles, research, case law, legal regulations, periodicals, and journals - to public records such as bankruptcies, liens, judgments, real estate records - to other types of information.

To manage, sort, link, and analyze billions of records within sub-seconds, LexisNexis designed a data intensive supercomputer built on our own high performing computing cluster (HPCC) platform that is proven for the past 12 years with customers who need to sort through billons of records. Customers such as leading banks, insurance companies, utilities, law enforcement and Federal government depend on LexisNexis technology and information solutions to help them make better decisions faster. The supercomputing platform is available as an open source solution called HPCC Systems®, and is an alternative to Hadoop. For more information visit

Speed and scale to solve big problems faster

Designed to manage the most complex and data-intensive analytical problems, HPCC Systems can process, analyze, and find links and associations in high volumes of complex data significantly faster and more accurately than current technology systems. HPCC Systems scales linearly from tens to thousands of nodes handling many petabytes (one petabyte equals 1,024 terabytes), supporting millions of transactions per day.

HPCC Systems delivers on a single platform, a single architecture and a single programming language for efficient processing.

Easy programming language offers less time, less code

The core of HPCC Systems is its Enterprise Control Language (ECL). ECL is a declarative, non-procedural data-centric programming language, highly optimized for large-scale data management and query processing. It automatically handles workload distribution across all nodes of the massively parallel HPCC clusters, enabling data analysts and data scientists to simply define the result requirements of their Big Data manipulation/analysis needs without worrying about implementation. For more information on HPCC and ECL, visit