A Roadmap for In-Memory Computing: Current and Emerging Use Cases
Explore how in-memory computing drives real-time analytics, scalability, and innovation across today’s data-intensive applications and emerging digital use cases.
- Why demand for IMC keeps growing
- Key real-world IMC use cases
- Emerging trends shaping the IMC future
- How Apache Ignite and GridGain compare
- Benefits of hybrid transactional/analytical processing
- Real-time performance for AI and ML
About this white paper
Modern enterprises face massive data growth, real-time customer expectations, and the need for faster decision-making. This white paper explores how in-memory computing (IMC) delivers the speed and scalability required to meet these challenges.
You’ll learn why organizations across industries are adopting IMC to unify transactional and analytical workloads, reduce latency, and power innovations such as streaming analytics, AI, and machine learning. The paper highlights current and emerging use cases, from adding speed to existing applications to enabling continuous learning and real-time decision automation.
It also details how Apache Ignite® and GridGain® lead the evolution of IMC through hybrid storage, SQL support, and distributed architecture — helping enterprises future-proof their infrastructure for the data-driven era.
In-memory computing is transforming data systems into real-time engines for analytics, AI, and continuous learning—enabling the next generation of digital business.
A Roadmap for In-Memory Computing: Current and Emerging Use Cases
Discover how in-memory computing powers real-time analytics, scalability, and AI. Learn current and emerging IMC use cases with Apache Ignite and GridGain.
Get the full white paper