ABOUT

The continual growth of real-time analytics use cases and a need to query both operational and historical data sets — where operations have to be completed in seconds rather than minutes, or milliseconds rather than seconds — has brought new challenges. We will look at how to utilise Gridgain as a bridge into real-time analytics for data lakes including Hadoop, enabling fast, scalable access to your data as well as the ability to run federated or cross-database queries where an operation joins data stored in both GridGain and Hadoop.