AIStor on ROSA
Lately, there has been a trend in the industry to bring data “closer” to home. The result is that organizations now want to keep their data on servers that they own, in their own datacenter or at a colocation provider.
Read moreLately, there has been a trend in the industry to bring data “closer” to home. The result is that organizations now want to keep their data on servers that they own, in their own datacenter or at a colocation provider.
Read moreAWS recently unveiled Amazon S3 Tables, claiming to optimize Iceberg analytics on S3. Yet, these "special buckets" mainly fix AWS's own limits—like request caps—not universal object storage issues. With AIStor, you get unmatched performance, no vendor lock-in, and no extra costs for table maintance.
Read moreAIStor's Prompt API transforms healthcare data—analyze MRI scans, uncover trends in medical records, and accelerate research with natural language prompts. From automating image analysis to streamlining patient care, it empowers better outcomes for providers, researchers, and patients
Read moreWe’ll dive deep into the network configurations with which you can configure AIStor to the different replication strategies and network topologies that can be used to ensure your data is stored and accessed efficiently across multiple AIStor deployments.
Read moreAlmost a year ago (actually 11 months ago), I wrote about the “Starving GPU Problem” and how the horsepower of Nvidia’s Graphic Processing Units (GPUs) could be so powerful that your network and your storage solution may not be able to keep up - preventing your expensive GPUs from being fully utilized. Well, in those short 11 months, a
Read moreTl;dr: GET, PUT, PROMPT. It’s now possible to summarize, talk with, and ask questions about an object that is stored on MinIO with just natural language using the new PromptObject API. In this post, we explore a few use-cases of this new API along with code examples. Motivation: Object storage and the S3 API’s ubiquity can be
Read moreToday we announced the launch of AIStor, a new release which represents our singular focus on building the world’s finest object store for AI/ML workloads. The AIStor represents a year of accelerated learning from our biggest customers. MinIO is operating at a different level than the rest of the industry. We have multiple clients with more than 100
Read moreThe object storage world to date has been defined by the S3 API concepts of PUT and GET. The world in which we live now, however, requires more. Given that MinIO has more S3 deployments than even Amazon, it fell to us to come up with the next great S3 API. That new API is the Prompt API and it
Read moreAs the demands of AI and machine learning continue to accelerate, data center networking is evolving rapidly to keep pace. For many enterprises, 400GbE and even 800GbE are becoming standard choices, driven by the need for high-speed, low-latency data transfer for AI workloads that are both data-intensive and time-sensitive. AI models for tasks like large language processing, real-time analytics, and
Read moreOne of the newest features of the AIStor is a private cloud version of the highly popular, open-source project, Hugging Face. This post details how AIStor’s AIHub effectively creates an API compatible, private cloud version of Hugging Face that is fully under the enterprise's control. Before we get started, it makes sense to introduce Hugging Face. Hugging
Read moreThe MinIO Console has been an evolving product for several years now. Every time we learn, we think about how to improve this incredibly important part of our interaction framework. First came the Console, which saw massive adoption within a year of its introduction. More than 10K organizations to be more specific.Next came the enterprise Console. That moved from
Read moreEnhance 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 moreDell 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 moreSimplifying 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 moreConfluent'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 moreMinIO 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 moreIn this post we’ll show you how quickly you can get a production grade of MinIO cluster up and running in just a few seconds. Not only that, but we’ll also show you how you can expand that cluster quickly in just a few seconds as well.
Read moreWe often talk about how good, fast and reliable access to data is paramount if you want to have an upper hand in your AI/ML game. Why is this the case? This is because hardware failures happen at different levels.
Read moreAmid the AI frenzy, one silent hero powers it all: modern object storage. It may not be glamorous, but it's the backbone of today's data lakes, enabling vast, efficient data management. Discover how AIStor elevates your data infrastructure.
Read moreThe modern enterprise defines itself by its data. This requires a data infrastructure for AI/ML as well as a data infrastructure that is the foundation for a Modern Datalake capable of supporting business intelligence, data analytics, and data science. This is true if they are behind, getting started or using AI for advanced insights. For the foreseeable future, this
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