AWS vs Database Mart: GPU Compute Price Comparison
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and Database Mart. Updated July 2026.
Provider Overview
Strengths & Best For
AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.
- Widest global region coverage
- Deep ecosystem integrations
- Enterprise SLAs
- Reserved instance discounts
Database Mart provides dedicated bare-metal H100, A100, and RTX GPU servers alongside cloud instances for AI, ML, and HPC workloads, with no virtualization overhead for maximum hardware performance. Monthly and on-demand billing options are available, making it suitable for both long-running training jobs and shorter inference workloads that need dedicated GPU hardware. A practical bare-metal GPU option for teams that need consistent, dedicated performance without shared-tenancy concerns.
- Dedicated hardware
- Flexible configurations
- Competitive pricing
Live GPU Pricing
Region Coverage
Popular Comparisons
AWS — hyperscaler provider
AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.
Database Mart — bare-metal provider
Database Mart provides dedicated bare-metal H100, A100, and RTX GPU servers alongside cloud instances for AI, ML, and HPC workloads, with no virtualization overhead for maximum hardware performance. Monthly and on-demand billing options are available, making it suitable for both long-running training jobs and shorter inference workloads that need dedicated GPU hardware. A practical bare-metal GPU option for teams that need consistent, dedicated performance without shared-tenancy concerns.
Billing model comparison
AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Database Mart uses Monthly / On-demand billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Database Mart's commitment requirement suits teams with predictable long-running jobs.
Which workloads each provider suits best
AWS is best suited for: Enterprise workloads, Production ML inference, Teams already on AWS. Its key strengths are widest global region coverage, deep ecosystem integrations, enterprise slas. Database Mart is best suited for: Dedicated GPU workloads, Long-running training, HPC. Its key strengths are dedicated hardware, flexible configurations, competitive pricing. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.
Support tiers and region coverage
AWS offers Basic → Enterprise support across 5 regions (us-east-1, us-west-2, eu-west-1 and 2 more). Database Mart offers Standard support across 1 region (US). AWS's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: AWS vs Database Mart
AWS was founded in 2006 and is headquartered in Seattle, WA. Database Mart was founded in 2015 and is headquartered in United States. AWS has 9 years more operational history than Database Mart, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.