Proven Architecture Reinforced for Resiliency, Scalability, and Performance;
Ensures Unprecedented Speed and Scale for AI Workloads
GridGain® announced version 9 of the GridGain Unified Real-Time Data Platform. Building on the proven multi-dimensional data processing and analytics capabilities of version 8, GridGain 9 delivers the most stable, resilient, and high-performant solution for ultra-low latency data applications, powering the extreme speed, scale, durability and reliability critical to modern enterprise use cases and AI.
According to Gartner®, “Data & Analytics teams continue to be challenged to design, deploy and manage an ecosystem of technology choices that is supported by a resilient and scalable technical architecture.”[1]
This is more true today than ever before. The explosion in real-time, data-intensive use cases – including the use of GenAI – for improved customer experiences, greater operational efficiency, and accurate decision-making, has put a focus on immediate and reliable data availability and accessibility across the enterprise.
With enhanced support for multiple data formats, models, and stores, including cloud data lakehouses, GridGain makes enterprise-wide data available for processing in real time, a key prerequisite for any AI-based initiative. GridGain 9 delivers the architectural resiliency and scalability necessary to power the data infrastructure foundation for large-scale, real-time data processing, AI and analytics applications.
“AI has shown the promise to deliver dramatic social and technological benefits. But it will never reach its full potential if businesses are unable to achieve the real-time insights, automations, and customer experiences they need,” said GridGain CEO, Eoin O’ Connor. “We have consistently evolved the GridGain platform to stay ahead of our customers’ data requirements, and we have again invested in reinforcing our solution to make it even more resilient and high-performant. The result is GridGain 9, a more powerful platform that will make it faster and easier to deliver new features, enhancements, and scalability to support modern application and AI use cases.”
Key Enhancements in GridGain 9
- Dynamic, on-demand scaling: GridGain 9 introduces new platform features, allowing users to scale its flexible in-memory and on-disk storage and processing capacity easily. GridGain’s industry-leading capabilities around dynamic scaling eliminate any impact on the overall system performance, even when users wish to extend their GridGain clusters to the cloud.
- Enhanced performance:GridGain 9 boosts efficiency by enhancing parallel, concurrent data processing and utilizing memory-centric storage engines tailored to the specific needs of various workloads, including analytics and AI.
- Stronger data integrity and consistency: With a more robust transaction management and consistency model for data – even in full SQL mode – GridGain 9 gives enterprises classic RDBMS capabilities with in-memory performance, making it easier to accelerate legacy applications and workloads.
- Improved developer experience: Intuitive and simpler APIs, improved cluster configuration, and devOps capabilities make it even easier for developers and DevOps engineers to build and manage highly scalable data-intensive applications using GridGain.
Additional Resources
- GridGain 9 product page
- GridGain blog: What’s New in GridGain 9
- GridGain blog: Accelerating Legacy RDBMS Systems with GridGain 9
- GridGain blog: Making Well-Informed AI-Driven Decisions in Real Time
[1] Gartner, Market Guide for AI and Data and Analytics Service Providers, Frances Karamouzis, Shubhangi Vashisth, Afraz Jaffri, 24 May 2023.
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