Compare AWS, Azure, and Google Cloud VM pricing across 100+ regions in a single view. No sales emails. No affiliate links. Just the real numbers, refreshed straight from each provider's pricing API.
Understanding cloud pricing is essential for optimizing infrastructure costs. These short briefs help you navigate the complex pricing structures of the major providers and pick the right model for each workload.
Cloud providers offer various pricing models to fit different needs. On-demand provides flexibility with pay-as-you-go rates. Reserved instances offer 30–60% discounts for 1-3 year commitments. Spot/Preemptible instances can save up to 90% but may be interrupted, making them suitable for fault-tolerant batch jobs.
General purpose instances balance CPU and memory for web servers and small databases. Compute optimized instances provide high CPU for batch and gaming. Memory optimized instances offer fast RAM for in-memory databases and analytics. Understanding workload requirements is key to cost optimization.
A multi-cloud approach distributes workloads across AWS, Azure, and Google Cloud. This prevents vendor lock-in, improves resilience, and lets you leverage each provider's strengths. Comparing prices across providers helps optimize costs while keeping flexibility.
Effective optimization combines technical and organizational work. Right-size instances to match actual usage — many orgs over-provision by 30–50%. Implement auto-scaling to adjust capacity to demand. Use reserved instances for predictable workloads and spot for interruptible tasks. Audit resources monthly to eliminate waste.
Cloud pricing varies 20–40% between regions. US East regions typically offer the lowest prices for AWS, while Western Europe tends to be more expensive. Consider data residency, latency, and compliance before choosing. For non-latency-sensitive workloads, a cheaper region can mean substantial annual savings.
On-demand suits unpredictable workloads and short-term projects. Reserved instances work best for production with predictable usage — commit 1-3 years for 30–72% savings. Spot offers the deepest discounts (up to 90%) but can be interrupted with 2 minutes notice — perfect for batch processing, CI/CD, and stateless tiers.
AWS, Azure, and GCP each have areas where they consistently come out ahead. Here's the honest breakdown so you know where to look first when designing your stack.
AWS offers the most extensive cloud infrastructure with 200+ services across 30+ global regions. EC2 instances range from micro to high-memory configurations. Key strengths: mature ecosystem, deep documentation, widest service portfolio.
Azure provides seamless integration with Microsoft enterprise tools and hybrid cloud capabilities. Virtual Machines support Windows and Linux with specialized series for different workloads.
GCP leverages Google's global network infrastructure for consistently low latency. Compute Engine offers custom machine types — letting you choose exact CPU and memory amounts.
Expert-written breakdowns to help you understand the platforms, optimize costs, and make decisions backed by data — not vendor decks.
Amazon EC2 offers over 750 instance types across multiple families designed for specific workloads.
Amazon EC2 remains the most widely used cloud computing platform, offering an extensive selection of instance types to match virtually any workload requirement. Understanding these options is crucial for optimizing both performance and costs.
The General Purpose family (T3, T3a, M5, M6i, M7i) provides balanced compute, memory, and networking resources. T3 instances use burstable performance, accumulating CPU credits during idle periods for use during spikes — ideal for web servers and development environments. M-series instances offer consistent performance for production applications.
Compute Optimized instances (C5, C6i, C7i) feature high-performance Intel and AMD processors optimized for batch processing, scientific modeling, gaming servers, and ML inference. These deliver the highest price-performance ratio for CPU-intensive applications.
Memory Optimized instances (R5, R6i, X2) provide fast access to large datasets in memory, essential for real-time analytics, in-memory caching, and high-performance databases. The X2 family offers up to 4 TB of RAM for SAP HANA and similar enterprise workloads.
Microsoft Azure offers specialized VM series for every workload, from burstable instances to HPC.
Azure's VM offerings span multiple series, each engineered for specific performance characteristics. The B-Series (Burstable) is the most cost-effective option for workloads that don't need continuous full CPU. Similar to AWS T3, B-series accumulate credits during idle periods.
D-Series and Dv5 represent Azure's general-purpose workhorses, offering balanced CPU-to-memory ratios with options for premium SSD storage. Dv5 features Intel Ice Lake processors with up to 96 vCPUs and 384 GB RAM.
F-Series prioritize high CPU performance with lower memory ratios, ideal for batch processing, gaming, and analytics. E-Series VMs provide high memory-to-CPU ratios for relational databases, in-memory analytics, and caching layers.
Azure's Hybrid Benefit lets customers with Windows Server licenses save up to 40% on Windows VM costs.
GCP's unique offering of custom machine types and automatic sustained-use discounts sets it apart.
Google Cloud Platform's Compute Engine differentiates itself through flexible machine configurations and automatic cost optimization features that don't require upfront commitments.
Unlike AWS and Azure, GCP allows custom machine types where you specify exact vCPU and memory amounts rather than choosing from predefined configurations. This prevents over-provisioning and can reduce costs by 15–30% for workloads that don't fit standard instance shapes.
Predefined machine types include E2 (cost-optimized general purpose), N2/N2D (balanced general purpose), C2/C3 (compute-optimized), and M1/M2/M3 (memory-optimized up to 12 TB RAM).
GCP's Sustained Use Discounts automatically reduce costs by up to 30% for instances running more than 25% of a month — no commitment required.
Common questions about cloud pricing, virtual machines, and how to actually keep your bill under control.
Our pricing data is updated regularly from official AWS, Azure, and Google Cloud APIs. Prices shown are estimates based on on-demand rates and may vary based on your specific configuration, region availability, and any applicable discounts or credits from your provider agreements.
Region (prices vary 20–40%), instance family (specialized instances cost more), operating system (Windows adds 40–50% over Linux), payment model (reserved saves 30–60%), and storage type (SSD costs 3-5x more than HDD per GB).
There's no single cheapest provider — it depends on your specific requirements. AWS often has competitive pricing for general workloads, Azure offers advantages for Windows-based systems, while GCP typically provides better sustained use discounts. Use our comparison tool to find the best option for your exact specifications.
Right-size instances to match actual usage, use reserved instances for predictable workloads, leverage spot for fault-tolerant jobs, choose optimal regions, implement auto-scaling, and regularly review and terminate unused resources. A multi-cloud approach can also help optimize costs.
A vCPU (virtual CPU) is a portion of a physical CPU core allocated to a VM. Most cloud providers define 1 vCPU as one hardware thread. A physical 8-core CPU with hyper-threading provides 16 vCPUs. Performance varies by provider and instance type, so benchmarking is recommended for performance-critical applications.
Choose SSD for databases, applications requiring low latency, and high IOPS workloads — typically 3-10x faster than HDD. Choose HDD for large storage volumes, backup/archive data, and sequential read/write operations where cost matters more than speed.
CloudMetrics was created by Alberto Gil Vicente as a free cloud pricing comparison tool. We aggregate real-time pricing data from Amazon Web Services, Microsoft Azure, and Google Cloud Platform to provide accurate cost comparisons — with no affiliate deals or hidden vendor bias.
Our mission is to simplify cloud cost optimization with transparent, up-to-date pricing. Whether you're migrating to the cloud, optimizing existing infrastructure, or evaluating multi-cloud strategies, CloudMetrics helps you find the best value for your specific requirements.