Real-time decision-making, instant personalization, fraud detection, and agentic automation all depend on one thing: your ability to move data fast, query it faster, and scale without breaking the system.
So let me say it plainly: VAST is the fastest analytics and AI platform on the planet. Full stop. No qualifiers.
Whether you’re running massive SQL queries, streaming sensor data into feature stores, or feeding GPU clusters for real-time inference—VAST delivers unmatched speed and linear scale. And we don’t get there with brute force. We get there with design.
Let’s walk through what makes this performance possible.
DASE Architecture: The Secret Behind Our Scale
It all starts with the DASE architecture. Unlike traditional systems that isolate storage and compute, or force you to shard and replicate data across silos, DASE gives every compute node direct access to the entire global dataset —no duplication, no rebalancing, no bottlenecks.
It’s a simple idea with massive consequences:
Your infrastructure doesn’t have to fight itself to scale.
DASE powers:
Linear performance scaling - just add compute, no tuning required
Single millisecond latency at exabyte scale
High availability with no hotspots, overprovisioning, or data movement
This is the architectural foundation that everything else builds on.
Then we store the data on…
All Flash Storage: No Tiering
Speed starts with storage and VAST doesn’t compromise. Our platform is 100% all-flash, delivering consistent low-latency access across every workload, from high-throughput analytics to sub-millisecond AI inference.
But this isn’t just “faster disks.” VAST’s flash layer is deeply integrated into our DASE architecture and NVMe-over-Fabrics fabric, so every compute node accesses flash directly. No tiers, no cache misses.
And unlike traditional all-flash systems, VAST delivers this performance at disk-era economics.
Here’s how:
We use ultra-low-cost commodity flash - the same hyperscale-grade media deployed in massive cloud environments.
We extend flash lifespan with intelligent data structures that align with SSD geometry, and a large SCM write buffer that absorbs and optimizes writes. This allows us to support flash for 10 years, radically improving TCO.
We minimize write amplification with a cluster-wide flash translation layer that manages SSDs like a unified hyperscale controller - reducing data movement and internal wear. Combine that with 32KB data chunks and global erasure coding, and you get the speed of memory, the resilience of disk, and the cost-efficiency of cold storage - all in one.
NVMe-over-Fabrics: Local Flash Speed, Global Reach
Most data platforms were built for spinning disks or local SSDs. We’re not most platforms.
VAST uses NVMe-over-Fabrics (NVMe-oF) to deliver high-speed access to all your data—across the entire cluster, from any compute node. NVMe-oF keeps things nearly as fast as local flash, but extends that performance over the network, making disaggregated architectures like DASE not just possible, but powerful.
This isn’t just about speeding up storage. It’s about making everything - data, metadata, and even transaction state - accessible from every CNode, in real time, without copies or coordination delays. NVMe-oF is what allows VAST to scale performance linearly, share everything efficiently, and eliminate the barriers between compute and storage.
Tiny Data Chunks: Scan Less, Do More
Sometimes the (literal) smallest design choices make the biggest impact. Our design choice to store data in 32KB chunks is orders of magnitude smaller than the 128MB to 1GB blocks used in formats like Parquet. We do this using something called a VAST Element, a fundamental building block of our storage layer.
Why does chunk size matter?
Because when a query runs, VAST scans only what’s needed - just the relevant bytes, no more. This dramatically reduces I/O and supercharges storage-side filtering, where most of the work is done before compute even gets involved.
In our benchmarks:
Filtering workloads run 10-20x faster than on object-backed storage systems
Warehouse-style queries see up to 30% acceleration, purely from improved scan efficiency before adding any acceleration
It’s a simple equation:
smaller chunks = less data scanned = faster results
VAST doesn’t just run queries fast—we avoid unnecessary work entirely.
Sorted Tables for Log-Time Search: From Bottleneck to Breakthrough
In most systems, even finding a single row means scanning an entire table or relying on brittle partitions and rigid indexes that fall apart at scale.
With our new Sorted Tables for Log-Time Search capability, VAST flips the script.
By simply sorting on ingest, VAST enables near-logarithmic query speeds (O(logN)) without the need for indexing, re-clustering, or partition tuning. Query latency stays low, even as data volumes grow into the billions of rows.
Take a look at this performance graph. This graph shows how query performance scales with table size. For Sorted tables (in blue), point query times remain nearly flat—even as the dataset grows from zero to 10 billion rows, response times stay close to zero milliseconds. In contrast, Unsorted tables (in red) show a steep, linear increase in query latency, rising from around 2,500 milliseconds to nearly 10,000 milliseconds as the row count increases—highlighting the dramatic performance benefit of sorted indexing.
Benchmarks show:
100x faster point lookups than unsorted tables
25x faster multi-key lookups across large datasets
Sub-millisecond retrieval of embeddings, features, and context for AI pipelines
And because it’s built natively into the platform, it’s simple to configure and works automatically.
Compute-Side + Storage-Side Acceleration: Best of Both Worlds
VAST doesn’t just move data faster; we make everything built on top of it faster too. Through our partnership with NVIDIA, we support GPU-accelerated Python and Spark via RAPIDS, enabling compute-heavy operations like joins, aggregations, and ML inference to run dramatically faster—often with no code changes.
While VAST accelerates data access, RAPIDS accelerates processing to unlock incredible results when used together. In real-world benchmarks, we’ve seen 14x faster fraud detection, 87% lower compute costs, and up to 400% performance gains over object-backed table formats. It’s a perfect pairing: fast data in, fast answers out.
The Fastest Platform for Data-Driven Intelligence
Intelligent systems can’t run on slow infrastructure. And with VAST, they don’t have to.
You no longer have to choose between performance, scale, and simplicity.
VAST delivers all three—fastest, most scalable, fully unified. No tradeoffs.
From real-time streaming to vector search to agentic AI and inference, we’re building the foundation for the next generation of AI and analytics.
Want proof? Let’s talk, either 1:1 or in a group setting.
