MinIO AIStor Integrates AWS S3 Express API for Enhanced AI Workloads

MinIO has announced the integration of AWS S3 Express API into its AIStor platform, offering enhanced performance for AI and data-intensive workloads without additional costs.

MinIO has announced the integration of Amazon's S3 Express API into its AIStor platform, announced in a press release. This integration aims to enhance performance for AI and data-intensive workloads by offering the benefits of the S3 Express API without the additional costs typically associated with AWS's S3 Express One Zone storage class.

The S3 Express API, introduced by Amazon Web Services in 2023, is designed to deliver maximum performance for AI and analytics workloads. MinIO's AIStor is the first AI data storage platform to adopt this API, enabling organizations to utilize its high-speed capabilities for all analytical and AI data without incurring extra costs. This includes support for accelerated PUT and LIST operations, new atomic append operations, and full disaster recovery and replication capabilities.

MinIO's integration of the S3 Express API allows enterprises to leverage high-performance data processing for applications such as data lakehouse analytics with Apache Spark and Iceberg, AI data pre-processing, and AI model training and inference. The platform also simplifies backend architecture by removing redundancies and implementing guardrails to improve developer experience and application security.

We hope you enjoyed this article.

Consider subscribing to one of several newsletters we publish like Silicon Brief.

Also, consider following us on social media:

Subscribe to Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

Market report

AI’s Time-to-Market Quagmire: Why Enterprises Struggle to Scale AI Innovation

ModelOp

The 2025 AI Governance Benchmark Report by ModelOp provides insights from 100 senior AI and data leaders across various industries, highlighting the challenges enterprises face in scaling AI initiatives. The report emphasizes the importance of AI governance and automation in overcoming fragmented systems and inconsistent practices, showcasing how early adoption correlates with faster deployment and stronger ROI.

Read more