Empowering Generative AI in Enterprises: Sustainable, High-Performance Storage Solutions with Global Data Fabric and Data Lakehouse

Rapid growth in unstructured data has triggered enterprises to shift from traditional file storage to scalable object storage solutions in their infrastructure. There has been a growing need to integrate both file and object storage into a unified platform capable of managing the complexities of traditional and modern data workloads. Gartner predicts that by 2029, over 80% of unstructured data will reside on consolidated storage systems—up from 40% in early 2024—highlighting the urgency of this transition. As sustainability takes center stage, businesses must adopt storage solutions that deliver both high performance and minimal environmental impact. This paper presents a storage solution designed for Generative AI and High-Performance Computing (HPC), addressing two critical requirements: 1. A unified high-performance storage solution that seamlessly integrates both file and object storage access. 2. A sustainable approach to building infrastructure that reduces energy usage and carbon emissions. We will explore how sustainable, high-performance storage solutions such as global data fabrics and data lakehouse technologies enable this vision. Key topics include: 1. The critical role of efficient storage in accelerating AI workloads. 2. The advantages of distributed file and object storage for enterprise-scale workloads. 3. Essential sustainability practices that align with environmental goals. 4. A global data fabric use case, leveraging features from reference architectures for research data, that incorporates these innovations as well as embedded sustainability practices. This paper demonstrates how researchers, architects, CIOs, and administrators can leverage next-generation storage solutions to improve operational efficiency and support sustainability in generative AI use cases.