In this white paper from GridGain Systems, you will learn how in-memory computing platforms such as Apache® Ignite™ and GridGain address:
- In-memory computing use cases which are driven by digital transformation
- The demands of IoT and machine learning for real-time processing
- The challenges of petabyte-scale in-memory computing applications
- Leveraging the latest developments in RAM and storage technologies such as non-volatile memory
What You Will Learn
As businesses cope with an explosion of data and users who expect real-time insights, many have turned toward in-memory computing solutions. As a result, in-memory computing platforms are becoming key infrastructure components for a growing number of organizations. In-memory computing platforms allow companies to keep their data in memory for maximum performance. They are also distributed computing platforms which allow users to easily, affordably scale out simply by adding nodes to the cluster. The platforms are also flexible infrastructure which is ready to support the coming waves of in-memory innovation.
The in-memory platforms of the future will embrace these trends and go further. Not only will they offer the key capabilities that users expect, such as strong SQL support, they will also address the needs of emerging use cases, such as IoT, machine learning, hybrid transactional/analytical processing (HTAP), and transformative new storage technologies such as non-volatile memory.
Based on insights from Jason Stamper of 451 Research and Nikita Ivanov, CTO of GridGain Systems, this white paper delves into these critical topics and discusses how Apache Ignite and GridGain are addressing them.