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