MariaDB Completes GridGain Acquisition to Power the Next Generation of Agentic AI
24.3.2026 14:00:00 CET | Business Wire | Press release
The acquisition creates the industry’s first AI-Ready Operating Platform – unifying transactions, analytics and in-memory speed to eliminate infrastructure fragmentation
MariaDB plc today announced the successful completion of its acquisition of GridGain Systems, Inc., the pioneer of in-memory computing and the force behind Apache Ignite. This strategic acquisition marks MariaDB’s move towards delivery of an AI-Ready Operating Platform, a unified system designed to handle the extreme-velocity data requirements of autonomous AI agents.
As enterprises transition from simple AI assistants to autonomous agentic systems that reason and act, traditional data layers are reaching a breaking point. By integrating GridGain’s in-memory technology, MariaDB now provides a single, high-velocity, persistent grounding layer that supports the entire AI lifecycle – from real-time data ingestion to complex reasoning.
“For the last 18 months, we have been building MariaDB for the agentic era,” said Rohit de Souza, CEO of MariaDB. “By bringing GridGain into the fold, we are delivering a unified platform that does the heavy lifting for the enterprise. We are removing the friction of manual data assembly and defining the high-velocity grounding layer that AI agents need to be truly useful – all backed by integrated support from a single company.”
Solving the Agentic Gap
The urgency for this platform is backed by industry shifts. Gartner® predicts, “40% of enterprise applications will feature task-specific AI agents by 2026 – up from less than 5% in 2025.”¹ Without a high-quality data foundation, “IDC warns that by 2027, companies that fail to establish high-quality, AI-ready data foundations will suffer a 15% productivity loss as generative and agentic systems falter” (IDC FutureScape 2026; Category: Worldwide Agentic Artificial Intelligence; Prediction 1).
MariaDB’s new platform addresses this inflection point by consolidating previously fragmented layers:
- Unified transactions & analytics: Run real-time analytics alongside live transactions on the same platform without the friction of ETL (extract, transform, load).
- In-memory velocity: Leveraging GridGain’s expertise to provide sub-millisecond response times for agentic workloads.
- Natively AI ready: Built-in vector capabilities to store, index and query embeddings, along with MCP server and integrations to AI frameworks, essential for building RAG workloads.
- Global scale: Technology to support AI deployments across hybrid and multicloud environments, with instant scaling.
The Agentic Shift: No Assembly Required
Instead of forcing developers to manually stitch together separate databases for memory, vector search and transactions, MariaDB now offers a “single pane of glass” for data. This reduces complexity, lowers total cost of ownership (TCO) and allows developers to focus on building agent logic rather than managing backend bottlenecks.
“Building for this level of scale today is like trying to build a high-speed machine out of a bucket of LEGOs – you have the pieces, but none of the pieces were meant to fit together under that kind of intensity,” said Vikas Mathur, chief product officer at MariaDB plc. “At AI-speed, the window for a response shrinks. A data platform like MariaDB no longer has seconds; it has single-digit milliseconds to deliver answers to agents. By providing a platform with a high-speed in-memory ‘baseplate’ already built-in, we eliminate the friction of manual assembly. We are giving developers a unified grounding layer that can handle the massive scale these agents demand.”
Looking Ahead: The Distributed Future
GridGain’s technology provides the foundation for the next phase of MariaDB’s evolution: a globally distributed data layer. As AI agents become autonomous and dispersed, the data they rely on must be as resilient and localized as the agents themselves. By extending the MariaDB Enterprise Platform into a distributed architecture, MariaDB ensures this grounding layer can scale across any region without sacrificing the sub-millisecond speed that machine-velocity workflows demand. This is a significant acceleration of MariaDB’s commitment to a world where machine-speed is the baseline.
A Year of Unstoppable Momentum
The completion of the GridGain acquisition is the latest milestone in a series of strategic moves to redefine the modern data stack for the AI era. Over the past 18 months, MariaDB has rapidly accelerated its innovation cycle, marked by MariaDB’s acquisitions and complete integrations last year of SkySQL (cloud/DBaaS) and Galera Cluster (high availability). MariaDB also recently launched MariaDB Enterprise Platform 2026, the industry’s first unified solution to feature native RAG-in-a-box pipelines and Model Context Protocol (MCP) support, allowing AI agents to communicate directly with enterprise data. In addition, last year the company launched MariaDB Exa, an extremely powerful analytics engine that enables near real-time analytics on transactional data without the need to ETL or move data.
This commitment to innovation has earned significant industry recognition. In the past year, MariaDB was honored with the 2025 DBTA Readers’ Choice Award for Best Overall Database and the 2025 AI TechAward for Best in Open Source AI. These accolades, combined with the introduction of native vector search and a new serverless cloud experience, solidify MariaDB’s position as the definitive high-velocity alternative to legacy database constraints.
Customer and Analyst Endorsements
“At Hatch, we ensure the timely delivery of some of the world's most complex engineering and construction projects. To manage this level of global scale, we moved beyond rigid and siloed legacy infrastructure to a data-centric platform,” said Tara Drover, CIO at Hatch. “By migrating to GridGain, we dramatically reduced our data processing times, transforming complex analysis and mid-project changes that once took minutes into near-instant outcomes. This is exactly the type of high-velocity capability we needed as we move toward an agentic future and deliver intelligent, predictive project management capabilities to our customers. We are excited to see GridGain become a foundational part of MariaDB, offering a unified platform that can support the next generation of autonomous and data-intensive workflows across the industries we serve.”
“MariaDB has been assembling a broader AI-ready platform through integrated vector search, the MariaDB Exa partnership for high-performance analytics, and the reacquisition of SkySQL to strengthen cloud delivery,” said Devin Pratt, research director, Data Management for IDC. “The GridGain acquisition extends that strategy into in-memory and real-time data processing, which may appeal to buyers seeking a more open alternative to fragmented or proprietary data stacks.”
Register for our upcoming webinar: Learn more about how MariaDB and GridGain are powering enterprise agentic AI strategies, by joining our joint webinar on April 8, 2026.
About MariaDB
MariaDB seeks to eliminate the constraints and complexity of proprietary databases, enabling organizations to reinvest in what matters most – rapidly developing innovative, customer-facing applications. Enterprises can depend on a single complete hybrid database platform for all their needs, that can be deployed in minutes for transactional, analytical, hybrid and AI use cases. Trusted by organizations such as Deutsche Bank, DBS, Nokia, Red Hat, Samsung and VirginMedia O2 – MariaDB delivers customer value without the financial burden of legacy database providers. For more information, please visit mariadb.com.
¹Gartner Press Release, Gartner Predicts 40% of Enterprise Apps Will Feature Task-Specific AI Agents by 2026, Up from Less Than 5% in 2025, August 2025, https://www.gartner.com/en/newsroom/press-releases/2025-08-26-gartner-predicts-40-percent-of-enterprise-apps-will-feature-task-specific-ai-agents-by-2026-up-from-less-than-5-percent-in-2025.
Gartner is a registered trademark of Gartner, Inc. and/or its affiliates and is used herein with permission. All rights reserved.
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