AI Data Workflows with Kafka and MinIO
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.
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Comparing Software Defined Storage with Appliances
Everybody claims to be a software company these days. From the nearly decade old pronouncement by Marc Andressen that “Software Is Eating the World” to the push from Wall Street to produce recurring software revenue; the pressure is on to claim - at least - that you are a software company. This is obviously problematic for appliance vendors. Try as
Read moreWorking with Small Objects in AI/ML workloads
Cloud-native AI/ML workloads push storage to the limit with many small files. AIStor combines metadata and data to optimize small file operations.
Read moreArchitect’s Guide to Migrating from Hadoop to a Data Lakehouse
Unlock real-time analytics, scalability, and future-proof your data with a lakehouse. Hadoop can't keep up with AI, but a lakehouse blends the best of data lakes and warehouses. Get actionable tips to smoothly phase your migration with minimal disruption.
Read moreCloud as an Operating Model - Not a Physical Location
We have said it before, but it bears repeating. The cloud is an operating model - not a physical location. That is why you will find MinIO everywhere on the public cloud, on the private cloud, at the edge. We don’t differentiate and because we are cloud native we are cloud (location) agnostic. The public cloud has mindshare and
Read moreTame the AI beast with Monitoring and Alerting
In this post we’ll show you how you visualize the cluster metrics in a web browser and also we’ll set up alerting so that when something like a drive needs to be replaced or drive runs out of space we can get alerted for it.
Read moreHiring for AI Success: Why Your First Hire Should Be a Data Engineer
To ensure AI success, start by hiring a data engineer, not an AI/ML expert. Learn from our experience and find out why a strong data foundation—focused on object storage, data lakehouses, and optimized pipelines—is critical for scalable, efficient AI/ML workloads.
Read moreOpen Source Begets Open Source: How Tesla is Accelerating AI
Tesla just open-sourced its Tesla Transport Protocol over Ethernet (TTPoE). Like Tesla’s earlier move to share EV patents, this opens the door to faster innovation through open-source contributions, proving once again that transparency drives progress.
Read moreIntroducing the MinIO Learning Subscription
Getting started with MinIO is easy—with a few simple commands and a small 100 MB binary, you can have a functional development environment up and running in no time. However, to harness the full capability of MinIO at production scale, professionals are encouraged to learn more about MinIO’s extensive capabilities. We are introducing the MinIO Learning Subscription, featuring
Read moreGit-like versioning for your AI Data
You’ve surely version controlled code in the past. But have you version controlled your data? Did you ever want to collaborate on large sets of data with various teams without committing a large chunk?
Read moreFrom Storage to AI Insights: Streamlining Data Pipelines with MinIO and Polars
Enhance your AI workflows by combining MinIO’s scalable AIStor with Polars, a lightning-fast DataFrame library. Learn how this powerful duo accelerates data pipelines, handles massive datasets, and offers powerful performance and scale.
Read moreWe Tried the Dell ObjectScale Community Edition, It Wasn’t Pretty
Dell generally focused on the filer game, but they dabble in object storage and have a very old offering, ECS. That makes sense, it was a step up from tape and wasn’t suited for dynamic workloads like HDFS modernization or database workloads. Needless to say, AI was out of the question. For a few years now, Dell has been
Read moreThe Power of Flexibility in the Modern Data Stack: The Data Lakehouse Advantage
Faced with skyrocketing compute costs, MinIO data scientist Archana Vaidyanathan leveraged the power of the data lakehouse, which allows for flexible compute choices without overhauling storage. AIStor enhances this model, delivering speed, scalability, and cost savings.
Read moreFrom Kafka to WarpStream: Simplifying Data Streaming with MinIO
Simplifying your data streaming architecture with WarpStream, a cloud-native, Kafka-compatible platform that cuts costs and complexity, recently acquired by Confluent. Paired with MinIO's high-performance object storage, it's a powerful alternative to Kafka for scalable, cost-effective streaming.
Read moreWhy Confluent’s WarpStream Acquisition Reinforces Object Storage as the Future of Data Streaming
Confluent's WarpStream acquisition highlights the future of data streaming built on object storage. WarpStream’s cloud-native design cuts costs by 85% over traditional Kafka. Believe the hype: object storage drives low-cost, scalable performance.
Read moreACID Transactions with Iceberg on AIStor
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.
Read moreLeading the Way: MinIO's Conditional Write Feature for Modern Data Workloads
MinIO introduced its conditional write feature long before AWS S3’s recent announcement. This powerful tool offers greater control in high-concurrency environments, ensuring data consistency and reliability, especially in AI and ML workflows.
Read moreStop Giving Your Data to Vendors
Databrick's CEO Ali Ghodsi Decouple storage and compute for more control, lower costs, and scalability. Modern datalakes, built on high-performance object storage like MinIO, empower you to handle AI/ML workloads with flexibility and performance—without relying on proprietary platforms.
Read moreMigrating from HDFS to AIStor
Take advantage of cloud native, Kubernetes-oriented, microservices-based architectures with object storage.
Read moreDatabases on Object Storage - the New Normal
When you think about object storage workloads and storage types - databases are increasingly a core workload. The changes are driven by two forces: the availability of high performance object storage and the explosive growth of data and specifically its associated metadata. Because of these two forces, almost every major database vendor now includes S3 compatible endpoints. Further, for many
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