Apache Ecosystem

Announcing General Availability of MinIO AIStor Tables

AIStor Tables is the first on-prem and hybrid data store to support Iceberg REST Catalog views. Iceberg views are catalog-native, engine-agnostic virtual tables that simplify access, enable versioning, and work across Spark, Trino, and more without an external catalog.

Apache Iceberg V3 boosts performance with deletion vectors that move delete costs to write time, row-level lineage for accurate incremental processing, variant types for efficient JSON queries, and native geospatial types with storage-level pruning. AIStor is the first to support V3.

The format war is over, and Iceberg won. Every major engine now supports it, from Snowflake to Spark. Built for object stores, Iceberg delivers scale, consistency, and simplicity. It is the unified foundation for enterprise AI and analytics. Future-proof your data with Iceberg.

AIStor Tables brings Iceberg catalogs natively into on-prem object storage. It simplifies data organization, enforces table-aware security, and lets AI teams catalog unstructured assets in structured tables, thereby enabling discovery.

The "big data king" that enterprises spent billions on is dying. Not from lack of trying, but because cloud-native alternatives now beat it at its own game. AIStor is faster and cheaper than HDFS. The revolution is happening in quarters, not decades.

Built a portable Java data pipeline using MinIO's AIStor and Kafka that scales from Mac to Kubernetes. Containerized stack (Kafka, AIStor, Prometheus, Grafana) processes millions of events, preserving raw data for analysis while delivering real-time dashboard summaries.

Cloud lakehouses break the bank at scale and compromise control. On-prem Iceberg lakehouses deliver speed, savings, and sovereignty. From cancer research to finance, real-world deployments prove it: petabyte-scale performance, full control, and lower TCO are within reach.

Choosing the right open table format—Apache Iceberg, Delta Lake, or Apache Hudi—can make or break your data lakehouse. This guide breaks down their strengths, how they integrate with object storage, and which one is best for AI, analytics, and real-time workloads.

Discover the power of Apache Iceberg and AIStor in transforming data lakehouses! From multi-engine compatibility to time travel, schema evolution, and blazing-fast performance, this guide dives deep into how Iceberg unlocks the full potential of modern AI and analytics workloads.

AIStor is a foundational component for creating and executing complex data workflows. At the core of this event-driven functionality is MinIO bucket notifications using Kafka.

Pairing the Iceberg table format with AIStor creates a powerful, flexible and extensible lakehouse platform. The Iceberg Table Spec declares a table format that is designed to manage “a large, slow-changing collection” of files or objects stored in a distributed system.

Take advantage of cloud native, Kubernetes-oriented, microservices-based architectures with object storage.

Explore modern data architecture with Iceberg, Tabular, and MinIO. Learn to seamlessly integrate structured and unstructured data, optimize AI/ML workloads, and build a high-performance, cloud-native data lake.

Explore the future of AI in an open-source landscape, challenging Big Tech's masked efforts. Learn how embracing extreme open innovation fosters collaboration, drives market growth, and sets the stage for an open-source AI data stack.

Joust against data complexity with LanceDB, a lightning-fast vector database optimized for AI/ML on the open-source Lance format. Teaming up with MinIO, it scales seamlessly, offering high-performance, cloud-native storage. Dive into the tutorial for a swift deployment.

The combination of StarRocks and MinIO offers a cloud-native, flexible, and efficient data architecture for modern enterprises, enabling independent scaling and optimized resource utilization. Read the full tutorial for insights into cloud-native analytics with StarRocks and MinIO

Unleash data collaboration and quality with Nessie! Learn to manage branches, commits, and merges effortlessly. This guide walks you through deploying Dremio, MinIO, and Nessie, transforming your data engineering with collaborative precision. Dive in to revolutionize your workflows!