The launch of Virtual Storage Platform One for Block, File, and SDS Cloud drove customer demand for simplified and streamlined hybrid cloud management.
Azure Blob Storage is an object storage service that is very similar to AWS S3. ActiveStorage from Rails has built-in support for both ActiveStorage and S3 for file storage, making it easy to integrate and even swap out providers. The Honeybadger Blog has already explored using S3 for file storage in Rails, and in this article, we'll explore using Azure to allow users to upload files in a Rails application. You can find the final code here on Github.
Recently launched Virtual Storage Platform One Block storage data platform receives top spot for exceptional energy efficiency and performance, setting an unmatched industry standard.
Thousands of customers have worked with Snowflake to cost-effectively build a secure data foundation as they look to solve a growing variety of business problems with more data. Increasingly customers are looking to expand that powerful foundation to a broader set of data across their enterprise.
The mid-sized enterprise is the fastest-growing market opportunity for data storage. But not just any storage system will do. These days, mid-sized enterprises must handle the complexities of unremitting data growth and distributed infrastructure, meet sustainability goals, manage the diverse storage needs of mission-critical applications, and respond to user requirements. Oh, and they need uninterrupted access to their data no matter what.
Virtual Storage Platform One Block empowers mid-sized enterprises to transform data management with breakthroughs in simplicity, security, and sustainability.
Report highlights the company's position as market leader in digital infrastructure sustainability innovation, and reinforces commitment to responsible business practices, people, and planet.
Unbreakable hybrid cloud platform seamlessly integrates structured and unstructured data, redefining data management efficiency and flexibility for enterprises.
Ozone enables ingest, processing, exploration, efficient iterative training, and fine-tuning of LLMs that rely on huge structured and unstructured datasets. This demo illustrates that. We have deployed a CML AMP chatbot that uses an LLM, augmented with an existing knowledge base. The knowledge base is stored in Ozone and retrieved over S3.