VAST + Cloudera: Build AI Factories on a Unified Data Foundation

Overview

The AI-Native Data Platform for Cloudera

Traditional enterprise architectures separate files, objects, data lakes, warehouses, vector databases, and AI infrastructure across multiple storage systems and data platforms. As organizations scale generative and agentic AI initiatives, these silos create governance challenges, increase infrastructure costs, and force teams to maintain complex pipelines simply to move data between systems.

Together, VAST and Cloudera modernize critical layers of the enterprise data platform. Cloudera delivers independently scalable data services for analytics, streaming, and AI, while VAST provides a scalable, high-performance data foundation optimized for modern analytics and AI workloads.

The result is a true single source of truth that reduces data movement, simplifies governance, and improves access to fresh enterprise data.

Single Source of Truth

Unify files, objects, tables, vectors, and event streams on a shared all-flash data foundation optimized for analytics and AI, reducing data movement, simplifying governance, and improving access to fresh enterprise data.

AI Performance

Deliver high-bandwidth, low-latency access to data for training, inference, and real-time analytics at scale, enabling AI and analytics workloads to operate against the same shared data foundation.

GPU Efficiency

Reduce storage-induced stalls and maximize utilization across training and inference infrastructure by delivering data efficiently to accelerators and minimizing contention across AI workloads.

Single Source of Truth

Unify files, objects, tables, vectors, and event streams on a shared all-flash data foundation optimized for analytics and AI, reducing data movement, simplifying governance, and improving access to fresh enterprise data.

AI Performance

Deliver high-bandwidth, low-latency access to data for training, inference, and real-time analytics at scale, enabling AI and analytics workloads to operate against the same shared data foundation.

GPU Efficiency

Reduce storage-induced stalls and maximize utilization across training and inference infrastructure by delivering data efficiently to accelerators and minimizing contention across AI workloads.

Building the Enterprise AI Factory

Most enterprises already have the data they need for AI. The challenge is unlocking the value in that data to create continuous pipelines for inference, fine-tuning, and analytics that power the next generation of intelligent applications.
Together, VAST and Cloudera are helping organizations build AI factories that connect data, intelligence, and infrastructure into a single operational platform for AI.

Jeff Denworth, Co-Founder, VAST Data

Co-Founder, VAST Data, VAST Data

Built for Enterprise and AI-Driven Workloads

Unified Data Foundation

Consolidate structured, unstructured, and vector data onto a shared platform that supports analytics and AI without introducing additional silos or copies.

AI-Optimized Infrastructure

Provide scalable throughput and low-latency access to data for training, inference, and fine-tuning workloads, enabling analytics and AI services to operate against the same high-performance data foundation.

Economics at AI Scale

Reduce storage overhead, lower TCO, and improve infrastructure efficiency across analytics and AI workloads while maximizing the return on storage, compute, and GPU investments.

Unified Data Foundation

Consolidate structured, unstructured, and vector data onto a shared platform that supports analytics and AI without introducing additional silos or copies.

AI-Optimized Infrastructure

Provide scalable throughput and low-latency access to data for training, inference, and fine-tuning workloads, enabling analytics and AI services to operate against the same high-performance data foundation.

Economics at AI Scale

Reduce storage overhead, lower TCO, and improve infrastructure efficiency across analytics and AI workloads while maximizing the return on storage, compute, and GPU investments.

Hybrid AI Infrastructure

Deploy analytics and AI services consistently across on-premises environments and public clouds while keeping data, models, and inference where performance, compliance, and cost requirements demand.

Real-Time AI Pipelines

Support streaming ingestion, vector retrieval, RAG, inference, and agentic AI workflows on a unified data foundation, eliminating data copies and reducing latency across the AI lifecycle.

Scale Inference Without Contention

VAST's Disaggregated Shared-Everything architecture allows every compute node to access the full shared data set directly, eliminating storage contention and enabling large-scale inference and KV cache workloads without east-west traffic.

Hybrid AI Infrastructure

Deploy analytics and AI services consistently across on-premises environments and public clouds while keeping data, models, and inference where performance, compliance, and cost requirements demand.

Real-Time AI Pipelines

Support streaming ingestion, vector retrieval, RAG, inference, and agentic AI workflows on a unified data foundation, eliminating data copies and reducing latency across the AI lifecycle.

Scale Inference Without Contention

VAST's Disaggregated Shared-Everything architecture allows every compute node to access the full shared data set directly, eliminating storage contention and enabling large-scale inference and KV cache workloads without east-west traffic.

From Data Silos to AI Factories

Traditional AI architectures rely on copies, pipelines, and disconnected systems that increase cost and slow innovation. Together, VAST and Cloudera create a unified data foundation where analytics and AI services operate directly on live enterprise data, simplifying governance and accelerating the path to production AI.

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Real-World Workloads. Production-Scale AI

Power analytics and AI initiatives on a single shared data foundation.

Generative AI and RAG

Build enterprise RAG applications using live enterprise data rather than stale copies and disconnected vector stores.

Support streaming ingestion and vector retrieval
Improve data freshness and governance
Reduce latency across retrieval and inference pipelines

Key Benefits

VAST + Cloudera: The AI-Native Data Platform

VAST and Cloudera provide a unified foundation for analytics and AI by combining enterprise data services with AI-native infrastructure optimized for real-time data access, large-scale inference, and agentic applications. Organizations can simplify operations, improve infrastructure efficiency, and accelerate the path to production AI.

Create a True Single Source of Truth

Eliminate data silos and reduce data movement by unifying files, objects, tables, vectors, and events on a shared platform that simplifies governance and improves access to live enterprise data.

Improve AI Infrastructure Efficiency

Reduce data path bottlenecks, improve GPU utilization, and maximize the return on AI infrastructure investments across training, inference, and analytics workloads.

Accelerate the Path to Production AI

Move from isolated AI experiments to production-scale AI systems that support real-time analytics, inference, RAG, and agentic workflows on a unified data foundation.

Create a True Single Source of Truth

Eliminate data silos and reduce data movement by unifying files, objects, tables, vectors, and events on a shared platform that simplifies governance and improves access to live enterprise data.

Improve AI Infrastructure Efficiency

Reduce data path bottlenecks, improve GPU utilization, and maximize the return on AI infrastructure investments across training, inference, and analytics workloads.

Accelerate the Path to Production AI

Move from isolated AI experiments to production-scale AI systems that support real-time analytics, inference, RAG, and agentic workflows on a unified data foundation.

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Solution Brief