MinIO Introduces GA of AIStor Tables, Unifying Enterprise Data for Agentic AI

Single high-performance data store for tables and objects is built for the scale, speed, and context that agentic AI and analytics demands

REDWOOD CITY, Calif.--(BUSINESS WIRE)--MinIO, the data foundation for enterprise analytics and AI, today announced the general availability of MinIO AIStor Tables. By unifying Tables and Objects in a single high-performance and Iceberg-native data store, AIStor eliminates structured and unstructured data silos to elegantly power any analytics, AI, and agentic workload at enterprise scale. With AIStor Tables, MinIO is demonstrating Open Table Format (OTF) leadership and is the first in the industry to build the full Apache Iceberg^TM V3 Catalog REST API directly into the data store. The general availability of AIStor Tables reflects MinIO’s ability to commit and deliver innovation for customers, building on the September 2025 AIStor tech preview. AIStor Tables is now available globally and can be deployed across on-premises, private, sovereign, and hybrid environments.

MinIO AIStor Tables unifies tables and objects in a single enterprise data store built for agentic AI. By eliminating the silos between databases and object storage, AI agents can analyze structured and unstructured data together, operating on complete, up-to-date enterprise data at massive scale and performance.

MinIO’s integration of Apache Iceberg V3 API into AIStor marks a fundamental shift in how enterprises may more easily prepare and leverage data for analytics and AI use. With the AIStor Tables capability, Apache Iceberg tables become first-class citizens within AIStor itself—inclusive of Views and Multi-table Transactions. This ensures customers can consistently and securely store and query across more of their data ecosystem faster and more efficiently, and execute atomic multi-table transactions with simpler, industry-compliant catalog. Unlike AWS S3 Tables, MinIO AIStor Tables is included natively in AIStor—helping customers reduce list-price storage costs by up to 40%.

“Analytics and AI infrastructures are no longer defined by compute alone. The data layer now determines how much enterprise AI value can actually be realized,” said AB Periasamy, co-founder and CEO of MinIO. “When structured and unstructured data are unified, AI systems can learn more, reason better, and deliver greater impact. Only an object-native architecture like MinIO AIStor can make that data fast, fluid, and ready for AI at scale. With AIStor Tables, we bring enterprise data together in a high performance data store that feeds analytics and AI systems directly.”

The High Performance Analytics and AI Data Store Where All Data Lives Together

AIStor’s Tables feature is an on-prem and hybrid-capable breakthrough for enterprises building modern data intelligence stacks. Tabular data and object data coexist within a single data plane and security model, scaling seamlessly from small datasets to exabyte-scale environments. This architecture allows enterprises to treat all enterprise data as AI data, increasing its value when analytics, data science, and AI workloads operate on the same authoritative source.

AIStor Tables complements up-stack compute across warehouse, lake, and lakehouse query engines, as well as emerging AI agents. Enterprises can run analytics, data science, and AI workloads directly on the same data with predictable performance, consistent governance, and cost efficiency, regardless of where the infrastructure is deployed.

Object-Native by Design for Highly Performant Enterprise AI

Enterprise AI and analytics workloads demand massive concurrency, predictable latency, and the ability to support mixed workloads at scale. Traditional storage architectures introduce operational complexity and performance constraints that limit how efficiently data can be used across these environments.

MinIO AIStor takes a different approach. Built with a minimalistic, software-centric design, AIStor uses an object-native architecture to maximize flexibility and performance while reducing operational overhead. This design enables seamless scalability across edge, on-premises, private, sovereign, and hybrid deployments. With AIStor Tables, these object-native advantages extend fully to structured data, allowing a single system to support analytics and AI workloads end to end.

The general availability of AIStor Tables follows a highly active tech preview program that attracted strong enterprise interest in unifying enterprise data for AI and analytics. Early adopters validated the need for an object-native approach to tables that simplifies operations while maintaining performance and control.

"By running analytics and AI workload directly on the same data, MinIO AIStor Tables fundamentally simplifies how we build and operate data pipelines,” said Conor Brennan, Managing Director Risk IT at Nomura. “It allows us to move faster, reduce operational complexity, DR recovery process, and treat all our data as first class.”

MinIO AIStor Tables is available today as part of MinIO AIStor. Enterprises can download and deploy directly from min.io.

Resources:

• Announcing General Availability of MinIO AIStor Tables
• MinIO Introduces GA of AIStor Tables
• The Case for Native Iceberg Catalog APIs and Unified Governance in Object Storage
• MinIO Introduces Iceberg Tables in AIStor, Unifying Enterprise Data for AI
• Apache Iceberg as the Foundation for Enterprise AI Data: Why MinIO Made Tables Native In AIStor

About MinIO:

MinIO is the data foundation for enterprise analytics and AI. Built for exascale performance and limitless scale, MinIO AIStor delivers a secure, sovereign, and AI-ready data store that spans from edge to core to cloud. With rampant adoption across the Fortune 100 and 500, MinIO is redefining how organizations and government agencies store, manage, and mobilize all of their data in the AI era. MinIO is backed by Jerry Yang's AME Cloud Ventures, Dell Technologies, General Catalyst, Index Ventures, Intel Capital, Softbank Vision Fund 2 and others.

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