One of the prominent information-centric, open source cluster systems that utilizes big data is developed by LexisNexis Risk Solutions; it is called HPCC. The HPCC system supports two types of processing techniques, as listed in the following points:

• Thor (parallel batch data processing): This is similar to the Hadoop MapReduce platform; it is an information refinery that holds the responsibility of maintaining huge volumes of raw data captured and performs ETL (extract, transform, and load) processing through it. Establishing information relations, processing algorithms for complex detail analysis, and identifying the key information for performance improvement are the key strengths of this system. The following is the architecture of the Thor processing cluster:

• Roxie (high-performance online query applications using indexed data files): This is like Hadoop with HBase and Hive capabilities added, and it acts as a rapid data delivery engine. This platform is an ideal architecture for data warehouse transportation and numerous online web service requests that have a similarity in their search query and rapid response systems. The following is the architecture of the Roxie platform:

Now let's review how Java as a programming language supports high-performance computing.