Modern enterprise AI initiatives are moving from experimentation to production-grade deployment. These efforts increasingly rely on unstructured data at scale, with workflows designed to sustain ongoing dataset creation and to reuse those datasets across multiple stages of the AI lifecycle, including training, inference, and retrieval-augmented generation (RAG). These shifts place new demands on the AI data layer and expose the limitations of storage-embedded architectures that treat data access, processing, and pipeline orchestration as external concerns. As a result, organizations are prioritizing data platforms that make federated data access and native processing fundamental platform capabilities.
Prowess Consulting researched how Dell™ AI Data Platform and VAST® AI OS address these challenges across architecture, data processing, RAG search, performance, and operational overhead. Our findings show that the integrated, GPU-accelerated Dell Technologies platform delivers notable advantages in functional breadth, GPU efficiency, pipeline simplicity, and end-to-end manageability. These differences can accelerate AI development cycles, reduce engineering effort, and create a more cost-effective path to production at scale.
TL;DR
Dell AI Data Platform brings together Dell PowerScale™, Dell ObjectScale™, and GPU-accelerated data engines that power a universal, enterprise-wide data layer, delivering consistent performance, governance, and scalability across every stage of the AI lifecycle. Dell Technologies and NVIDIA provide performance numbers such as 12× faster vector indexing, 3× faster data processing, and 19× faster time-to-first-token compared with traditional CPU-based workflows.
Evidence: See the “Processing and Acceleration” section.
FAQ
Q: What is the main difference between Dell AI Data Platform and VAST AI OS?
A: Dell AI Data Platform is an open, modular, federated data platform that lets you keep data where it already lives and that accelerates the full AI data lifecycle with GPU‑powered data engines, whereas VAST AI OS is a single storage-bound stack that requires ingesting/migrating outside data into its proprietary environment, and that is still maturing toward full lakehouse capabilities.
Evidence: See the “Two Solution Paths: Different Approaches to the AI Data Layer” section.
Q: How does Dell AI Data Platform impact AI performance?
A: Dell Technologies and NVIDIA report dramatic performance gains across key AI data‑processing steps due to deep integration with NVIDIA® GPUs and CUDA‑X™ libraries:
- Up to 12× faster vector indexing
- Up to 3× faster data processing
- Up to 19× faster time‑to‑first‑token (crucial for LLM responsiveness)
Evidence: See the “Processing and Acceleration” section.
Q: What advantages does Dell AI Data Platform offer for RAG and search use cases?
A: Dell Technologies offers broader RAG and search advantages, such as in-place federated access, hybrid keyword/vector retrieval, and platform-wide GPU acceleration, while VAST AI OS depends on a siloed, platform-centric architecture with a limited footprint across broader data center infrastructure.
Evidence: See the “Search and RAG Workloads” section.
Q: How does Dell AI Data Platform reduce integration and operational overhead?
A: The open, federated Dell Technologies platform avoids re‑platforming and “data‑pull‑in” workflows, whereas the VAST AI OS platform‑centric model hinges on migrating data into its stack, which can introduce additional integration and operational effort.
Evidence: See the “Operational Considerations” section.
Q: Which types of organizations are best suited for Dell AI Data Platform versus VAST AI OS?
A: The Dell Technologies platform is designed for environments where data lives across file, object, software-as-a-service (SaaS), cloud, and on‑premises systems, and where teams want to avoid forced re‑platforming or wholesale data migration. Its openness, hybrid search, and platform‑wide GPU acceleration suit enterprises that prioritize interoperability, flexibility, and incremental modernization. By contrast, VAST Data’s approach aligns with customers who are comfortable restructuring existing data pipelines around a single vendor’s substrate.
Evidence: See the “Matching Solutions to Business Needs” and “Conclusion” sections.