Big Data Management

Clustering Capabilities

• A load balanced OLAP architecture to scale up processing capability
• In-memory computing and custom pagination to project large datasets to the end user

NoSQL based OLAP

• Move past the OLAP engine constraint of querying RDBMSes by implementing NoSQL querying capability
• MDX to NoSQL translation will bring to the table the Big Data framework benefits
• MongoDB document stores and HBase based solutions
• Hadoop/Spark frameworks used to aggregate large data-sets, to service end user queries

In-memory cache

• Fast Cache grid implementation using Redis
• Stores large datasets for the MDX queries
• Significant improvement in performance when data is preloaded as part of the BoD/EoD ETL run