The data storage landscape is undergoing a transformational change. AI is changing how systems need to handle both large amounts of data and the speed at which that data can be processed. Where enterprise organizations once depended on traditional SAN/NAS architectures, the explosive growth of unstructured data, now measured in petabytes, has made one thing clear – object storage has become the dominant technology for enterprise storage needs.
To help better understand how IT leaders are leveraging object storage, MinIO, Inc., the company behind the popular open-source cloud storage software MinIO, has announced the findings of its Object Storage and AI Report. The report also reveals how AI is reshaping adoption and workload patterns.
The findings of the report were based on a survey of 600+ IT and software development leaders on storage, AI, workloads, and infrastructure. The survey was conducted by MinIO in partnership with UserEvidence.
The MinIO report shows that more than 70% of enterprises’ cloud-native data was in object storage, and this percentage is expected to grow. Enterprise leaders forecast that 75% of their cloud-native data will be in objective storage within two years.
The top three factors for this explosive growth include the support offered by AI, performance requirements, and scalability. These three reasons are interlinked, as AI initiatives demand performance at scale, making object storage the ideal solution to handle large volumes of data efficiently.
So how exactly do enterprises use object storage? The survey reveals that the top three use cases include advanced analytics, AI model training, and data lakehouse storage.
“This research confirms what MinIO, AWS, Azure, and Google already know – that object storage is the storage technology of the cloud – public, private, or edge,” said Jonathan Symonds, Chief Marketing Officer, MinIO.
“What is more interesting, however, is the expected acceleration of adoption, driven by GenAI workloads. Modern object stores are uniquely qualified to meet the demands of these workloads – namely throughput performance, immutability, and exascale. We are keen to watch this research evolve as enterprises build new storage architectures to support their AI ambitions.”
While AI support has been vital to the growth of object storage, 96% of the respondents shared that they are facing challenges due to AI. These challenges largely stem from the need to manage vast volumes of unstructured data and ensure consistent performance at scale, both of which are crucial for supporting AI workloads effectively.
IT leaders cited security and privacy (44%), data governance (27%), and cloud-native storage (25%) as the three biggest challenges to AI success in their organization.
The report indicates a growing trend toward a hybrid cloud approach for AI and machine learning (ML) workloads. While the public cloud remains popular, 68% of the respondents shared that they are concerned about the cost of running AI workloads, and they are considering a hybrid cloud approach.
This trend aligns directly with MinIO’s capabilities, as its object storage is designed to support both public and private cloud environments. However, organizations will need to carefully assess how to balance cost and performance in this evolving landscape.
“This work represents one of the most comprehensive looks at the AI storage landscape and there are some eye-opening findings”, noted Ray Rhodes, co-founder at UserEvidence. “IT leaders are clear in their preference for object storage – a finding that transcended company size or geography. We look forward to partnering with MinIO on more research in this key area.”
AB Periasamy, the co-founder and co-CEO of MinIO
Earlier this year, MinIO shifted its focus from a general-purpose storage solution to an AI-centric platform with the launch of AIStor. The platform included features such as promptObject API, enabling natural language queries of unstructured data, and high-speed RDMA support for seamless GPU integration.
MinIO was launched in 2014 to address the demands of unstructured data growth. From zero lines of code in 2014, to 1.5 billion docker downloads with deployments across the globe, it is now a popular choice for open-source object storage. MinIO co-founder and CEO, Anand Babu (AB) Periasamy, is a BigDataWire People to Watch 2018.
The AIStor launch directly aligns with the themes in MinIO’s Object Storage and AI Report, as both emphasize the critical role of object storage in supporting AI workloads. With AI adoption accelerating and enterprises rethinking storage, the report’s findings suggest object storage will be crucial for meeting the scale and performance needs of modern AI.
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