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Multi-Site Replication Global Identity and Access Management Encryption Bucket & Object Immutability Bucket & Object Versioning Data Life Cycle Management & Tiering Automated Data Management Interfaces Monitoring Scalability AWS S3 Compatibility
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Modern Datalakes Modern, multi-engine datalakes depend on object stores that deliver performance at scale. Learn more about this core MinIO use case. AI&ML Object storage is powering the AI revolution. Learn how MinIO is leading that effort with performance at scale. Integrations Browse our vast portfolio of integrations SQL Server Discover how to pair SQL Server 2022 with MinIO to run queries on your data on any cloud - without having to move it. Commvault Learn how Commvault and MinIO are partnered to deliver performance at scale for mission critical backup and restore workloads. Snowflake Query and analyze multiple data sources, including streaming data, residing on MinIO with the Snowflake Data Cloud. No need to move the data, just query using SnowSQL. Splunk Find out how MinIO is delivering performance at scale for Splunk SmartStores Veeam Learn how MinIO and Veeam have partnered to drive performance and scalability for a variety of backup use cases. HDFS Migration Modernize and simplify your big data storage infrastructure with high-performance, Kubernetes-native object storage from MinIO. VMware Discover how MinIO integrates with VMware across the portfolio from the Persistent Data platform to TKGI and how we support their Kubernetes ambitions.
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The Disruptive Nature of Data Lakehouses

Keith Pijanowski Keith Pijanowski on Apache Iceberg
The Disruptive Nature of Data Lakehouses

Introduction In 1997, Clayton Christensen, in his book The Innovator’s Dilemma, identified a pattern of innovation that tracked the capabilities, cost, and adoption by market segment between an incumbent and a new entrant. He labeled this pattern “Disruptive Innovation.” Not every successful product is disruptive - even if it causes well-established businesses to lose market share or even fail

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Digging Deeper into Iceberg: ACID Transactions on Tables

Matt Sarrel Matt Sarrel @msarrel Matt Sarrel on Apache Iceberg
Digging Deeper into Iceberg: ACID Transactions on Tables

The Apache Iceberg data lake storage format enables ACID transactions on tables saved to MinIO. ACID transactions enable multiple users and services to concurrently and reliably add and remove records atomically. At the same time, queries are isolated to maintain read consistency against tables that are in the process of being altered. You can put MinIO and Iceberg, in conjunction

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