GPU-Accelerated PostgreSQL

"Cluster performance. Single-node simplicity."

Read the Docs

cupug.com

GPU Accelerated Databases are Here

10B+ Row Tables Now Common

Traditional systems can't handle enterprise analytical data

$2M+ Annual Warehouse Costs

Distributed clusters require massive infrastructure spend

30%+ YoY Cost Growth

Cloud warehouse spend spiraling with no end in sight

Postgres is the #1 database among AI professionals — 59.5% developer adoption (Stack Overflow 2025)

The Future of Postgres on NVIDIA

PostgreSQL Extension

GPU-accelerated analytics that stays in the Postgres ecosystem. No migration, no retraining. Standard extension with no code forks.

NVIDIA SCADA Technology

GPU-direct storage access eliminates CPU bottlenecks. First to productize for Postgres.

Single-Node Scale

Performance that rivals multi-node clusters without the operational complexity.

DRAM IOPs for NVMe Costs

GPU-Direct storage fabrics can saturate NVMe systems, beating DRAM IOPs.

BEFORE 16 Node Cluster

Complex • Expensive • Fragile

AFTER 1 Node + cupug

Simple • Affordable • Reliable

How It Works

Traditional (CPU-Centric)

CPU orchestrates all storage I/O
Bulk reads and writes only
GPU idles waiting on CPU for data
Network shuffle between nodes dominates query time

cupug (GPU-Centric via SCADA)

GPU threads directly initiate storage I/O
Fine-grained, sparse reads — fetch only bytes needed
Massive thread parallelism hides storage latency
No network shuffle — all data local on NVMe

Result: Fine-grained, on-demand data access with massive parallelism on random-access workloads

Key Use Cases

Ad-hoc queries on 10B+ row tables
Real-time dashboards without pre-aggregation
ML feature store with historical depth
Hybrid OLTP/OLAP workloads on a single server
Data-dependent queries without I/O amplification

Tick-level financial data and risk modeling
CDR and network telemetry analytics
Clickstream and recommendation pipelines
Genomic and clinical trial queries
IoT sensor telemetry and predictive maintenance

TCO Comparison

Metric	16-Node Cluster	cupug (1 Node)	Advantage
Compute Cores	2,048	80,000	39x
Data Access Rate	3,200 GB/s	32,000 GB/s (HBM)	10x
Interconnect	100 Gbps	2,000 Gbps	20x
Storage IOPs	3-4M	40-200M	50x

CLUSTER ANNUAL TCO $850K-$1.15M

Compute + Storage + Operations

COST REDUCTION 8x

Better performance, fraction of cost

CUPUG ANNUAL TCO $106K-$150K

Single server + 4x B200 GPUs

Target Customers

Financial Services

Tick data, risk modeling, real-time compliance

Telecommunications

CDR analytics, network telemetry

E-commerce / AdTech

Clickstream, recommendations, ML features

Life Sciences

Genomic queries, clinical trials

IoT / Industrial

Sensor telemetry, predictive maintenance

Logistics / Supply Chain

Route optimization, inventory forecasting, tracking