Solution Brief

MinIO AIStor Tables

About This Resource
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Who This is For:

Data engineers, AI platform architects, and analytics teams building agentic AI systems or unified data architectures that require Iceberg-native table access alongside unstructured object storage.

Key Takeaways
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Enterprise data is fragmented across databases, filesystems, and object stores — a problem that becomes critical as agentic AI systems need to traverse structured and unstructured data simultaneously.

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AIStor Tables is the first on-prem object store with a built-in Apache Iceberg Catalog API, eliminating the need for separate catalog infrastructure and enabling SQL queries directly on object storage.

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With Iceberg established as the winning open table format across all major analytics engines, AIStor Tables positions on-prem object storage as a first-class participant in the modern data stack.

Enterprise data is splintered across databases, filesystems, and object stores, a fragmentation that becomes a hard constraint as agentic AI systems need to traverse structured and unstructured data simultaneously. AIStor Tables addresses this directly: it is the first object-native, on-premises object store with a built-in Apache Iceberg Catalog API, eliminating the need for separate catalog infrastructure and enabling SQL queries directly on object storage. This solution brief covers the architecture of AIStor Tables, the advantages of object-native Iceberg integration versus a separate catalog service, and the use cases it unlocks for AI and analytics teams, including unified discovery across transactions, documents, call logs, and customer records from a single store. It also addresses the broader table format landscape: Iceberg has emerged as the dominant open standard across all major analytics engines, and AIStor Tables positions on-premises object storage as a first-class participant in that ecosystem.

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