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Adkhabar > Blog > News > MinIO Introduces Iceberg Tables in AIStor, Unifying Enterprise Data for AI
MinIO Introduces Iceberg Tables in AIStor, Unifying Enterprise Data for AI
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MinIO Introduces Iceberg Tables in AIStor, Unifying Enterprise Data for AI

Last updated: 01/10/2025 10:36 AM
Published: 01/10/2025
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New capability establishes MinIO as the on-prem Exascale AI Data Store for secure, sovereign, scalable Enterprise AI

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REDWOOD CITY, Calif., Sept. 30, 2025 /PRNewswire/ — MinIO, the leading exascale object store for Enterprise AI Data, today announced the addition of native Apache Iceberg support to its flagship AIStor offering via a powerful new Tables feature. By integrating the Iceberg Catalog API directly into MinIO AIStor, MinIO is helping enterprises unlock more value from AI on their own terms with an AI Data Store that brings together structured and unstructured data under a single, open standard. 

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While Iceberg has emerged as the de facto standard for enterprise AI and analytics, resolving years of format fragmentation, it has traditionally been considered primarily a tool for analytics on structured data – until now. With AIStor’s native Iceberg implementation, enterprises can now unify all their structured and unstructured data – whether tables, transactions, images, audio and more – into a single, coherent fabric. The resulting foundation strengthens the efficacy of AI workloads from analytics to agentic AI, because AI can now act on all enterprise knowledge, not just a subset.

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Enterprises sit on massive volumes of data, but turning it into AI value has been costly and complex. Iceberg is the new standard, yet managed cloud services drive up expenses and on-prem solutions with external catalog services create operational headaches. By embedding Iceberg natively, AIStor Tables makes data fluent, fast, and AI-ready, removing layers of cost and complexity from data and infrastructure management while ensuring consistency, security, and scale.

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As the only object-native on-premises object store with the Apache Iceberg REST catalog built-in, AIStor unifies tabular and object data to power agentic AI and lakehouse analytics. Just as MinIO brought the Amazon S3 experience to every data center, MinIO is now doing the same for Iceberg with AIStor Tables—making the enterprise AI standard available at scale, on premises. MinIO designed the Tables feature to address the challenges exascale AI customers face today in building Iceberg-powered workloads as well as repatriating such workloads from the cloud to cut costs while strengthening privacy, sovereignty, and control.

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“Data is the currency of AI, but enterprises are struggling with its enormous scale and variation,” said AB Periasamy, co-founder and co-CEO of MinIO. “Iceberg is the clear standard for enterprise AI data. The challenge is that most on-prem implementations make it harder than it needs to be, requiring separate catalog databases and extra layers of infrastructure that add cost and operational risk. By building Iceberg directly into AIStor, we take away that complexity and give enterprises a simple, scalable foundation for AI. This not only lowers costs and speeds progress, but also ensures AI can reach its full potential because all data is AI data.”

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With its native Iceberg Catalog API, MinIO AIStor Tables transforms how enterprises use data, confidently breaking away from the limits of traditional storage and enabling AI to scale without compromise. This will unlock key breakthroughs for scalable Enterprise AI, including:

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  • A Unified View of the Business: Bringing together structured and unstructured data into a single Iceberg-based foundation, ensuring AI has access to all enterprise knowledge for more accurate insights and decisions.
  • Seamless Ecosystem Fit: Built on open standards, AIStor Tables works out of the box with existing tools and query engines including Spark, Trino, Dremio, and Starburst, protecting past investments while accelerating new AI initiatives.
  • Reduced Risk and Faster Time to Value: Native design eliminates separate catalog service infrastructure, security models, and management overhead of traditional Iceberg deployments, so enterprise AI scales more efficiently.
  • Complete Sovereignty with Savings: Runs in the private cloud to keep sensitive data secure and compliant, while reducing dependency on hyperscalers and lowering long term AI infrastructure costs

The introduction of AIStor Tables reflects MinIO’s broader evolution from object storage to AI Data Store pioneer. In the new AI economy, data strategy defines leadership. MinIO gives enterprises the tools to unify, govern, and accelerate their data fabric, on premises, at any scale. This transforms AIStor from an object store into the foundational AI Data Store that agentic AI demands, unifying years of siloed data into a single, governable platform.

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AIStor Tables is available immediately in tech preview.

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Resources:

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  • Apache Iceberg as the Foundation for Enterprise AI Data: Why MinIO Made Tables Native In AIStor



  • AIStor Tables: Technical Deep Dive


  • The Case for Native Iceberg Catalog APIs and Unified Governance in Object Storage

  • From Data Swamps to Reliable Data Systems: How Iceberg Brought 40 Years of Database Wisdom to Data Lakes

About MinIO:
MinIO is the data foundation for enterprise 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 billions of downloads and 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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Logo – https://mma.prnewswire.com/media/2360095/MinIO_Logo.jpg 

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Media Contact:
Tucker Hallowell
MinIO@inkhouse.com

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View original content:https://www.prnewswire.co.uk/news-releases/minio-introduces-iceberg-tables-in-aistor-unifying-enterprise-data-for-ai-302570186.html

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