July 24 Webinar: Enabling Real-Time Analytics for Hadoop Data Lakes with GridGain

Enabling Real-Time Analytics for Hadoop Data Lakes with GridGainJoin GridGain's Denis Magda July 24 at 11 a.m. Pacific to learn how Apache® Ignite™ and GridGain® -- as an in-memory computing platform -- can modernize existing data lake architectures, enabling real-time analytics that spans operational, historical, and streaming data sets. Register now for this free, live event.

A data lake is a system or repository of data stored in its natural/ raw format, usually object blobs or files. Data lakes, such as those powered by Hadoop, are an excellent choice for analytics and reporting at scale.

Hadoop scales horizontally and cost-effectively and fulfills long-running operations spanning big data sets. However, the continual growth of real-time analytics requirements — where operations need to be completed in seconds rather than minutes, or milliseconds rather than seconds — has brought new challenges to Hadoop based solutions.

In this session, Denis will explain how:

  • How to choose the right deployment mode and responsibilities when working with GridGain and Hadoop
  • How to determine which operations should be handled by GridGain and which should be sent to Hadoop
  • How to use Spark DataFrames to run federated (aka cross-database) queries that span GridGain and Hadoop
  • How to perform initial data loading from Hadoop to GridGain
  • How to set up bi-directional synchronization between Hadoop and GridGain

Register today to reserve your spot!