Apache Kafka is an open-source distributed event streaming platform that is used for building real-time data pipelines and streaming applications. It was originally developed by LinkedIn and is now maintained by the Apache Software Foundation. Kafka is designed to handle high volume, high throughput, and low latency data streams, making it a popular choice for building scalable and reliable data
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We are back with another educational course in our rapidly expanding repertoire on our YouTube channel. This month, MinIO’s Will Dinyes is discussing Object Management for those who have set up their object store and want to learn more about how to set up an efficient and sustainable data lifecycle management strategy.
This 11-part series spanning just over an
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Build your on-prem data lake with Apache Iceberg, Dremio and MinIO
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Learn how to get started with Dremio and MinIO on Kubernetes for fast, scalable analytics.
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In this post we’ll talk about Erasure Coding and Erasure Sets, and then dive deeper into how to use the Erasure Code Calculator when designing deployments to make the most out of MinIO by opting for the right hardware configuration setup from the get go.
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After listening to community feedback, we feel as if an update is warranted on a number of fronts including Weka. We wanted to take the opportunity to clarify some language we used - specifically around revocation.
At the outset we want to make clear:
Any company is free to use MinIO’s licensed code for commercial purposes, even for competitive
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Let's review some of the tools available to get data out of S3, local FileSystem, NFS, Azure, GCP, Hitachi Content Platform, Ceph, and others, and into MinIO clusters.
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In this blog post, we will build a Notebook that uses MinIO as object storage for Spark jobs to manage Iceberg tables.
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Learn how MinIO simplifies and streamlines the generation and assignment of TLS certificates for services running on Kubernetes.
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What if you had a personal health monitor that kept tabs on your well-being, without any effort on your part? Imagine a system that tracks your health daily, highlighting even the slightest problems, so that you can seek help before minor issues become major concerns.
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GitLab can use MinIO as its object storage backend to store large files such as artifacts, Docker images, and Git LFS files. Given the right underlying hardware, MinIO provides the performance and scale to support any modern workload, including GitLab.
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At MinIO, we are dedicated to the principles of open source software. From the beginning, we’ve remained committed to this philosophy and that’s why you will find that the upstream and the commercial code are exactly the same. We are obligated to protect our software - particularly from companies that package it in their proprietary products and pass
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We’ve joined forces with Rafay to develop this tutorial to show you how to make the most of multi-cloud Kubernetes using Rafay to deploy, update and manage Kubernetes and applications using MinIO for object storage.
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When it comes to storing and managing data, there is the modern, cloud-native way and there is the traditional, appliance oriented way. Needless to say, object storage is the modern, cloud-native way. While it would be simple to suggest that MinIO is hopelessly biased towards object storage (it is, afterall, the only thing we do), that would miss a key
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MinIO's Object Lambda implementation allows for the transformation of your data to serve unique data format requirements on an application-by-application basis. For example, a dataset created by an e-commerce application might include personally identifiable information (PII). When the same data is processed for analytics, PII should be redacted. However, if the same dataset is used for a marketing
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Apache Spark and MinIO are powerful tools for data lakes and analytics. Learn how to run them in Kubernetes.
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This post focuses on some of the features associated with this unique model and is the second in a series that details the features and capabilities that come with a commercial relationship.
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The double whammy of inflation (and correspondingly high interest rates for the foreseeable future), demand destruction and an uncertain outlook have companies aggressively looking for cost savings. Now.
While reducing headcount is a current play for most of the tech industry, there is real money in the data stack. Every company is a data company at this juncture - it
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We live in a cloud-native world where edge architecture must be consistent with cloud architecture, and where data can be retrieved with the same API call regardless of where it lives.
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