VAST AI Operating System for Analytics

Unified Real-Time Analytics Infrastructure for the AI Era

Modernize fragmented analytics environments with a single platform for data lakes, lakehouses, streaming, ETL, analytics, and AI. The VAST AI Operating System unifies structured, unstructured, and vector data with real-time performance, simplified operations, and enterprise-scale efficiency.

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Browse Customer Stories

The Analytics Infrastructure Challenge

Outgrowing Fragmented Analytics Architectures

Traditional analytics platforms were built for batch processing, disconnected data silos, and separate infrastructure stacks. As analytics and AI converge, these architectures create operational complexity, unpredictable performance, and rising infrastructure cost.

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Complimentary Conference Pass

Attend VAST Forward as a speaker, on us. Last year's event was the must-attend gathering for AI and data leaders, selling out well ahead of the show.

Speaker Networking

Connect with the practitioners tackling the same challenges you are, across infrastructure, applications, and research.

Reach an Influential Technical Audience

Present your ideas to AI infrastructure leaders, platform engineers, architects, researchers, and practitioners driving the next generation of enterprise AI.

Amplified Visibility

Get promoted across VAST Forward marketing and event channels, putting your session in front of the broader VAST community.

Our BI tools would only be able to see the data as it was 12 hours ago. We want our data to be as current as possible. If you can get low latency on your data, you can make it operational, not just analytical.

Aaron Pritchard

Technical Team Lead, Evodian

Why Now

The Architecture Shift Reshaping Enterprise Analytics

The shared-nothing architectures behind most data warehouses, Hadoop clusters, and data lakes were never designed for the scale, concurrency, and continuous data flows of modern analytics and AI. As data grows across cloud, on-premises, and edge environments, fragmented platforms become increasingly expensive, complex, and difficult to manage.

At the same time, analytics has shifted from batch reporting to continuous intelligence. Streaming analytics, vector search, AI inference, and automated pipelines require immediate access to structured, unstructured, and vector data without the latency and complexity of disconnected systems.

VAST's Disaggregated Shared-Everything (DASE) architecture changes the economics of enterprise analytics by unifying storage, database, streaming, and compute on a single flash-native platform. The result is real-time insights, continuous intelligence, and AI-driven automation at exabyte scale without sacrificing flexibility, governance, or simplicity.

The Architecture Shift Reshaping Enterprise Analytics

The VAST AI Operating System

One Unified Platform for Analytics, Streaming, and AI

The VAST AI Operating System collapses fragmented analytics infrastructure into a unified, real-time platform built for the AI era. By integrating the VAST DataStore, DataBase, Event Broker, and DataEngine on VAST’s Disaggregated Shared Everything architecture, VAST eliminates data movement, simplifies operations, and accelerates analytics and AI workloads at massive scale.

Consolidate

Unify data lakes, lakehouses, warehouses, streaming systems, ETL pipelines, and vector databases into one flash-native platform with a single governance model.

Accelerate

Powered by DASE, VAST DataBase combines real-time transactional ingest with flash-native columnar analytics, delivering consistent low-latency performance for analytics, streaming, and AI.

Simplify

Eliminate external Kafka clusters, Spark sprawl, fragile ETL pipelines, and operational silos with an integrated platform for data and compute.

Scale

Scale linearly from terabytes to exabytes across structured, unstructured, streaming, and vector workloads without rearchitecting.

Use Cases

Explore Analytics use cases

Discover how VAST accelerates modern analytics workloads, from real-time event streaming and AI automation to high-performance lakehouse analytics.

Event-Driven Analytics and AI

Build real-time event architectures that unify streaming, analytics, and AI automation on a single platform.

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The Three Pillars of Modern Analytics

Solve the Hardest Challenges in Enterprise Analytics

Modernize Legacy Analytics Infrastructure

Legacy Hadoop environments and tiered storage architectures create operational complexity, inconsistent performance, and rising infrastructure cost. VAST replaces fragmented storage silos with a unified, all-flash platform that consolidates structured, unstructured, and streaming data into a single namespace. SyncEngine automates migration and tiering from Hadoop, cloud object stores, and legacy environments — enabling organizations to modernize analytics infrastructure without disruptive rip-and-replace projects.

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Modernize Legacy Analytics Infrastructure

Accelerate Analytics and Query Performance

Traditional lakehouse architectures struggle under large-scale analytical workloads, forcing constant tuning, partitioning, and compute scaling. VAST DataBase eliminates these bottlenecks with a flash-native architecture optimized for real-time analytics. Features like Sorted Tables and Co-Located Joins dramatically reduce I/O overhead and query latency, enabling faster analytics with fewer compute resources and predictable performance at any scale.

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Accelerate Analytics and Query Performance

Real-Time Streaming Analytics and Event-Driven Pipelines

Traditional analytics platforms rely on batch ETL processes that move data through multiple systems before it can be analyzed, creating latency, complexity, and stale insights. VAST enables a fundamentally different model with an event-driven architecture that continuously captures, processes, and analyzes data as it arrives. Built on the VAST Event Broker and DataEngine, organizations can automate data pipelines, trigger transformations, and update analytics in real time delivering continuous intelligence and faster decision-making.

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Real-Time Streaming Analytics and Event-Driven Pipelines

What does VAST DataBase help enterprises do?

Accelerate Real-Time Analytics with VAST DataBase

VAST DataBase combines the transactional speed of modern databases with the scalability and analytical power of a lakehouse architecture. Built on the DASE architecture, it delivers real-time ingest, low-latency analytics, vector search, and continuous updates in one unified system — eliminating the limitations of fragmented analytics infrastructure.

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Real-time Analytics Performance

Built on VAST's Disaggregated Shared-Everything (DASE) architecture, VAST DataBase combines high-speed transactional ingest with flash-native analytical performance. Data is ingested continuously and stored in an optimized columnar format, enabling real-time analytics, low-latency queries, and efficient execution at massive scale without data movement or performance bottlenecks.

Unify SQL and Vector Search

Run analytical queries and semantic search on the same data within VAST DataBase. Structured data, metadata, and vectors are stored together in a single platform, eliminating data duplication, synchronization pipelines, and external vector databases.

Event Topics to Tables

Kafka topics are automatically stored as VAST DataBase tables, making live event streams instantly available for analytics. Eliminate complex streaming pipelines and analyze real-time and historical data together from a single platform.

Scale Without Bottlenecks

Scale analytics workloads to exabyte scale and trillions of vectors with flash-native performance and no performance drift.

What does DataEngine help enterprises do

VAST DataEngine is a programmable, event-driven compute layer that transforms analytics infrastructure into an intelligent, automated platform for real-time data processing. By executing compute directly where data lives, DataEngine simplifies ETL, streaming analytics, and AI pipeline orchestration.

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Build and Automate Data Pipelines

Create event-driven workflows that connect data ingestion, transformation, analytics, and AI processes. Use triggers and serverless functions to automate end-to-end pipelines without external orchestration tools.

Transform Data In Place

Execute serverless Python functions directly on the platform to cleanse, enrich, join, and transform data where it resides, eliminating data movement, batch ETL jobs, and reducing external Spark clusters.

Stream and Analyze Data Continuously

Use the VAST Event Broker in DataEngine to unify real-time streaming, analytics, and AI pipelines within a single platform. Eliminate disconnected Kafka clusters, streaming infrastructure, and data pipelines while enabling continuous intelligence on live and historical data.

Observe and Optimize Pipelines

Monitor pipeline performance, throughput, and operational efficiency through a unified management and observability layer.

Use Cases

Modern Analytics in Action

The VAST AI Operating System powers real-time analytics, operational intelligence, and AI-driven decision making across industries that demand scale, performance, and simplicity.