Latest release strengthens hybrid analytical and transactional processing to fully unlock real-time AI
PALO ALTO, Calif., May 13, 2025 – GridGain, provider of the only unified real-time data storage and processing platform for transactional, analytical and AI workloads, today announced the general availability of GridGain Platform 9.1 which boasts enhanced support for real-time hybrid analytical and transactional processing. With this latest release GridGain is able to execute analytical workloads simultaneously with ultra-low latency transactional processing, as well as feature extraction and the generation of vector embeddings from transactions, to optimize AI and RAG applications in real time.
With version 9.1, GridGain introduces advanced analytics capabilities and eliminates the need for separate transactional and analytical systems, as well as slow and fragile ETL pipelines. GridGain 9.1 offers performance, flexibility, and scalability by combining enhanced column-based processing (OLAP) and row-based processing (OLTP) in a unified architecture. Key benefits include real-time decision-making on fresh data, reduced infrastructure and operational complexity, and optimized TCO of cold/historical data storage and access.
“GridGain’s advanced analytics capabilities – including federated queries across columnar and row stores and segregated workloads to minimize noisy neighbors – help to make GridGain the best platform for real-time AI and analytics,” said Lalit Ahuja, CTO of GridGain. “Our continued innovation in these areas are why leading companies depend on GridGain to accelerate the AI, transactions and analytics that enable their critical applications such as real-time risk analysis and fraud detection, real-time dashboards, dynamic pricing, and high-stakes operational analytics.”
GridGain 9.1 further complements the platform’s powerful transactional capabilities. Not only does GridGain support scalable full ACID compliance; it goes one step further and provides configurable strict consistency, allowing enterprises to determine and configure their cluster appropriately for their specific use cases.
The Platform serves as a feature or a vector store, enabling real-time feature extraction or vector embedding generation from streaming or transactional data, thus ensuring the availability and readiness of all relevant data in real time for AI. Additionally, GridGain can act as a predictions cache, serving pre-computed predictions or running predictive models on demand. For Generative AI, GridGain provides a robust foundation for real-time Retrieval-Augmented Generation (RAG) applications. It integrates with open-source tools and libraries, such as LangChain and Langflow, as well as commonly used language models. These features, built on GridGain’s powerful and proven data storage and processing engine, help to make GridGain a leading enabler of real-time AI.
Additional Resources
GridGain blog: Real-Time Analytics Without Trade-Offs: GridGain 9.1
GridGain blog: From Real-Time Transactions and Analytics to GenAI Applications: Why GridGain Is Built for What’s Next
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About GridGain
GridGain provides the only unified real-time data storage and processing platform for transactions, analytics and AI. Brought to you by the original creators of Apache Ignite, the GridGain platform combines a fast distributed ACID-compliant multi-model database with the execution of AI, analytical and transactional workloads in real time, with unlimited horizontal scalability and high availability. With GridGain, users can deliver all relevant data and analytics to their most demanding applications at low-millisecond latencies and massive scale. GridGain is trusted by leading companies like Citi, Barclays, RBC, American Airlines, AutoZone, and UPS to accelerate their existing applications, speed operational analytics, risk analysis and fraud detection, power AI operations, and provide fast-access data hubs. To learn more, please visit www.gridgain.com.
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CONTACT:
Brigit Valencia
For GridGain Systems
Brigit@compel-pr.com
360.597.4516
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