Amazon Web Services (AWS) is the world's most widely adopted cloud platform, offering over 200 fully featured services spanning compute, storage, databases, networking, machine learning, analytics, and more. AWS pricing is notoriously complex—costs are driven by a combination of service selection, usage volume, data transfer, storage tiers, support plans, and architectural decisions. Unlike traditional software with per-seat pricing, AWS bills based on consumption across dozens of potential cost centers, making accurate budgeting and cost optimization critical for buyers.
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This guide combines AWS's published pricing with Vendr's dataset and analysis to break down Amazon Web Services pricing in 2026, including:
Whether you're evaluating AWS for the first time or preparing for renewal, this guide is designed to help you budget accurately and negotiate with clearer market context.
AWS pricing varies dramatically based on which services you use, how much you consume, and what commitment level you choose. There is no single "AWS price"—instead, costs are determined by:
A small startup might spend $500–$5,000 per month on basic compute and storage, while mid-market companies commonly see $10,000–$100,000+ monthly, and enterprises often commit to multi-million-dollar annual agreements.
Benchmarking context:
Vendr's dataset shows that AWS pricing outcomes vary widely based on commitment structure and negotiation approach. Get your custom AWS price estimate to see what similar companies pay for your specific usage profile.
AWS doesn't offer traditional "tiers" like SaaS products. Instead, pricing is structured around commitment models and support plans that layer on top of your actual service consumption.
On-Demand is AWS's pay-as-you-go model with no upfront commitment. You pay published rates for each service you consume, billed by the second, hour, or GB depending on the service.
Pricing Structure: On-Demand pricing is the baseline rate card. For example, a t3.medium EC2 instance in US East costs approximately $0.0416/hour ($30/month if running continuously), while S3 Standard storage costs around $0.023/GB/month for the first 50 TB. Rates vary by region, instance type, and service.
Observed Outcomes: On-Demand offers maximum flexibility but typically represents the highest per-unit cost. Most organizations use On-Demand for variable or unpredictable workloads, while committing to Reserved Instances or Savings Plans for steady-state usage. Vendr data shows that companies relying primarily on On-Demand often pay 30–50% more than those who optimize with commitments.
Benchmarking context: Even without long-term commitments, buyers can negotiate better outcomes through Enterprise Discount Programs. Compare AWS commitment models with Vendr to understand potential savings for your usage pattern.
Reserved Instances (RIs) offer discounts of 30–70% compared to On-Demand in exchange for 1- or 3-year commitments to specific instance types and regions.
Pricing Structure: RIs require you to commit to a specific instance family, size, and region. Payment options include All Upfront (highest discount), Partial Upfront, or No Upfront. A 3-year All Upfront RI for a t3.medium might cost around $10–$12/month (versus $30 On-Demand), representing roughly 60–65% savings.
Observed Outcomes: RIs work well for predictable workloads but lack flexibility—if your architecture changes, you may be locked into unused capacity. Vendr transaction data shows that buyers who carefully model their steady-state usage before committing to RIs often achieve 40–60% cost reductions on compute, though over-commitment can erode those gains.
Benchmarking context: RI purchasing decisions should be informed by actual usage patterns and growth forecasts. Vendr's AWS pricing tool helps model RI scenarios against your projected consumption.
Savings Plans offer similar discounts to RIs (up to 70% off On-Demand) but with more flexibility. You commit to a consistent dollar amount of usage per hour (e.g., $10/hour) for 1 or 3 years, and AWS applies discounts to eligible services.
Pricing Structure: Compute Savings Plans apply to EC2, Fargate, and Lambda across any region or instance family. EC2 Instance Savings Plans offer slightly higher discounts but are limited to a specific instance family and region. Like RIs, payment options include All Upfront, Partial Upfront, or No Upfront.
Observed Outcomes: Savings Plans have largely replaced RIs as the preferred commitment model for many buyers due to their flexibility. Vendr data indicates that mid-market and enterprise buyers commonly commit 60–80% of their baseline compute spend to Savings Plans, reserving the remainder for On-Demand to handle spikes and experimentation.
Benchmarking context: Determining the right Savings Plan commitment level requires balancing discount depth with flexibility. See what similar companies commit based on Vendr's anonymized AWS transaction data.
EDPs are custom agreements negotiated directly with AWS, typically for organizations committing $100,000+ annually (often $1M+ for meaningful discounts). EDPs provide percentage discounts across your entire AWS bill in exchange for multi-year spending commitments.
Pricing Structure: EDP discounts are negotiated case-by-case and apply as a percentage off your total monthly invoice. Discounts typically range from 5–15% for smaller commitments, scaling to 20–30%+ for multi-million-dollar agreements. EDPs often include additional benefits like extended payment terms, credits for migration or training, and dedicated account support.
Observed Outcomes: EDPs are where the most significant AWS savings occur for enterprise buyers. Vendr transaction data shows that companies with $500K+ annual spend who negotiate EDPs often secure 15–25% off their total bill, with larger enterprises achieving 25–35% discounts when combining EDPs with Savings Plans and volume leverage.
Benchmarking context: EDP negotiations are highly variable and depend on commitment size, growth trajectory, competitive pressure, and timing. Vendr's AWS negotiation intelligence provides percentile-based benchmarks for EDP discount rates by spend tier and contract structure.
AWS offers four support tiers that layer on top of your service consumption costs:
Pricing Structure:
Observed Outcomes: Most production workloads require at least Business Support for 24/7 access and faster response times. Enterprise Support is common for organizations spending $100K+/month who need architectural guidance and a TAM. Vendr data shows that support costs typically add 3–10% to total AWS spend depending on usage tier and support level.
Benchmarking context: Support tier selection should align with your operational maturity and risk tolerance. Compare AWS support costs against similar deployment sizes in Vendr's dataset.
AWS costs are driven by a complex interplay of service selection, usage patterns, architectural decisions, and commitment strategy. Understanding these drivers is essential for accurate budgeting and cost optimization.
Service consumption: Your choice of services and how heavily you use them is the primary cost driver. Compute (EC2, Lambda, ECS/EKS), storage (S3, EBS, Glacier), databases (RDS, DynamoDB, Aurora), and data transfer each contribute differently. A compute-heavy workload might see 50–70% of costs in EC2 and related services, while a data-intensive application might allocate 30–50% to storage and databases.
Instance and resource sizing: Choosing the right instance types, storage classes, and database configurations directly impacts costs. Over-provisioning (e.g., running larger instances than needed) can inflate bills by 30–50%, while under-provisioning risks performance issues. Right-sizing is an ongoing optimization exercise.
Data transfer and egress: Data transfer costs are often underestimated. Egress to the internet costs $0.09/GB for the first 10 TB/month (decreasing with volume), while cross-region transfer costs $0.02/GB. For data-heavy applications, transfer fees can represent 10–20% of total spend.
Commitment model: On-Demand, Reserved Instances, Savings Plans, and EDPs each offer different cost profiles. Organizations that optimize their commitment mix—covering baseline usage with Savings Plans or RIs and using On-Demand for variable workloads—typically achieve 30–50% lower costs than those relying solely on On-Demand.
Support and premium services: Support plans (3–10% of spend), premium services like AWS Shield Advanced, AWS WAF, and third-party marketplace solutions add incremental costs. These are often necessary for production environments but should be factored into total cost of ownership.
Regional pricing variation: AWS pricing varies by region. US East (N. Virginia) is typically the lowest-cost region, while regions like Asia Pacific (Sydney) or South America (São Paulo) can cost 20–50% more for equivalent services. Multi-region architectures multiply these costs.
Benchmarking context: Understanding your cost drivers is the first step toward optimization. Vendr's AWS cost analysis helps identify where your spend concentrates and where negotiation or architectural changes can yield savings.
AWS's consumption-based model creates numerous cost centers that buyers often overlook during initial budgeting. Planning for these hidden costs prevents budget overruns and sticker shock.
Data transfer and egress fees: Data leaving AWS (egress to the internet or other cloud providers) incurs charges that can add 5–15% to total costs for data-intensive workloads. Cross-region and cross-AZ transfer also adds up. Many buyers underestimate these costs during migration planning.
Support plan costs: While Basic Support is free, production workloads typically require Business Support (3–10% of monthly spend) or Enterprise Support ($15K/month minimum or 3–10% of spend). These costs are often excluded from initial estimates but are essential for operational readiness.
Premium services and add-ons: Services like AWS Shield Advanced ($3,000/month), AWS WAF (per-rule and per-request fees), CloudFront (CDN costs), and Route 53 (DNS query fees) add incremental costs. Third-party marketplace solutions (monitoring, security, backup) also layer on top of core AWS spend.
Storage class and retrieval fees: While S3 Standard storage is straightforward, using Glacier or Glacier Deep Archive for archival introduces retrieval fees that can be expensive if you need to access data frequently. Intelligent-Tiering adds a small per-object monitoring fee.
Database and compute overhead: RDS charges separately for instance hours, storage, backup storage, and I/O operations. Multi-AZ deployments double instance costs. Read replicas add incremental instance and storage costs. These can increase database costs by 50–100% compared to single-instance deployments.
Licensing and BYOL complexity: Some services (e.g., RDS for SQL Server or Oracle) include license costs in the hourly rate, which can be significantly higher than open-source alternatives. Bring Your Own License (BYOL) options exist but add procurement and compliance complexity.
Training and migration costs: AWS offers credits for training and migration in some EDP agreements, but these are negotiated benefits, not defaults. Budget for internal training, potential consulting fees, and migration tooling if moving from on-premises or another cloud.
Benchmarking context: Hidden costs can inflate total AWS spend by 20–40% beyond core service consumption. Vendr's AWS pricing tool helps model total cost of ownership including these often-overlooked fees.
AWS spending varies dramatically by company size, workload type, and optimization maturity. Vendr's dataset provides directional guidance on what organizations commonly pay.
Small businesses and startups ($500–$10,000/month): Early-stage companies typically start with basic compute (a few EC2 instances or serverless functions), S3 storage, and managed databases. Monthly costs often range from $500 for minimal workloads to $5,000–$10,000 as usage scales. These buyers usually rely on On-Demand pricing with minimal commitments.
Mid-market companies ($10,000–$100,000/month): Organizations with established production workloads commonly spend $10,000–$100,000 monthly. At this scale, buyers typically adopt Savings Plans or Reserved Instances to cover 50–70% of baseline usage, achieving 20–40% cost reductions compared to pure On-Demand. Support costs (Business Support) add 5–10% to the total.
Based on anonymized AWS transactions in Vendr's platform over the past 12 months:
Enterprise organizations ($100,000+/month): Large enterprises with complex, multi-service deployments often spend $100,000–$1M+ monthly. These buyers negotiate Enterprise Discount Programs (EDPs) with multi-year commitments, achieving 15–35% discounts on total spend. Combined with Savings Plans and architectural optimization, total effective discounts of 40–60% versus On-Demand are common.
Vendr data shows that enterprise buyers with $1M+ annual commitments often secure 20–30% EDP discounts, with the largest agreements (multi-million-dollar commitments) reaching 30–40% off total bills. Enterprise Support adds $15K–$50K+/month depending on usage tier.
Benchmarking context: Your actual AWS costs will depend on your specific service mix, usage patterns, and negotiation approach. See what similar companies pay for AWS based on percentile-based benchmarks from Vendr's transaction data.
AWS pricing is highly negotiable, especially for organizations with significant spend or growth potential. Vendr's dataset reveals consistent patterns in successful AWS negotiations.
AWS negotiations hinge on your ability to commit to future spend. Before engaging AWS sales, analyze your current monthly run rate, identify optimization opportunities, and build a realistic 12–36 month growth forecast. AWS rewards growth commitments—buyers who can credibly project 50–100%+ annual growth often secure better EDP terms than those with flat or declining usage.
Vendr data shows that buyers who enter negotiations with detailed usage analysis and conservative growth projections achieve better outcomes than those who over-commit and later struggle to meet minimums.
If your annual AWS spend exceeds or will soon exceed $100,000, request an EDP. EDPs provide percentage discounts across your entire bill in exchange for multi-year spending commitments. Start the conversation early—AWS sales cycles for EDPs can take 60–90 days.
Based on anonymized AWS deals in Vendr's dataset:
Negotiation guidance: Vendr's AWS negotiation playbook provides supplier-specific tactics, timing strategies, and leverage points based on observed deal outcomes.
EDPs discount your total bill, but you can stack additional savings by committing to Savings Plans or Reserved Instances for predictable workloads. This layered approach—EDP discount applied to already-discounted Savings Plan rates—can yield total effective discounts of 50–65% versus On-Demand.
Vendr transaction data shows that buyers who combine EDPs with 60–80% Savings Plan coverage achieve the deepest overall savings, while maintaining flexibility for variable workloads.
AWS is most flexible when facing competitive pressure. Mentioning active evaluations of Microsoft Azure, Google Cloud Platform, or Oracle Cloud Infrastructure (OCI) signals that you have alternatives. Even if you prefer AWS, demonstrating that you've modeled costs on competing platforms strengthens your negotiating position.
Buyers who present credible multi-cloud or hybrid-cloud strategies often secure better EDP terms, extended payment terms, or additional migration and training credits.
Beyond percentage discounts, negotiate payment terms (Net 60 or Net 90 instead of Net 30), migration credits (AWS often provides credits to offset migration costs from on-premises or other clouds), and training credits (for AWS certifications and professional services). These non-discount concessions can add significant value, especially for organizations undergoing cloud transformation.
Competitive benchmarks: Compare AWS pricing against Azure and GCP to understand where AWS is competitively vulnerable and where you have leverage.
AWS sales teams operate on quarterly and annual quotas. Negotiations initiated in the final 4–6 weeks of a quarter (especially Q4, ending December 31) often yield better terms as reps work to close deals. However, avoid appearing desperate—position your timeline as flexible but with a clear decision date.
Vendr data shows that buyers who engage AWS 60–90 days before their target start date, with a stated decision deadline aligned to quarter-end, often achieve 3–8 percentage points better EDP discounts than those who negotiate mid-quarter or rush the process.
AWS respects buyers who demonstrate cost discipline. Before negotiating, implement basic optimizations: right-size over-provisioned instances, delete unused resources, adopt Savings Plans for steady-state workloads, and use S3 Intelligent-Tiering for storage. Showing AWS that you're a sophisticated buyer who manages costs actively strengthens your credibility and negotiating position.
These insights are based on anonymized AWS deals in Vendr's dataset across a wide range of company sizes and contract structures. Buyers can explore these insights directly using Vendr's free pricing and negotiation tools:
AWS competes primarily with Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud Infrastructure (OCI). While feature parity exists across most core services, pricing structures, discount models, and total cost of ownership differ meaningfully.
| Pricing component | Amazon Web Services | Microsoft Azure |
|---|---|---|
| On-Demand compute (baseline) | t3.medium ~$30/month (Linux, US East) | B2s ~$30/month (Linux, East US) — similar baseline |
| Reserved Instance / Reserved VM discount | 30–70% off On-Demand (1- or 3-year RIs or Savings Plans) | 30–72% off On-Demand (1- or 3-year Reserved VMs) |
| Enterprise discount programs | EDP: 10–35% off total bill for $100K–$1M+ annual commits | EA (Enterprise Agreement): 10–30% off total bill for similar commits |
| Support costs | Business: 3–10% of spend; Enterprise: $15K/month minimum or 3–10% | Professional Direct: ~$1K/month; Premier: custom, often $15K–$50K+/month |
| Estimated total for $50K/month usage | $30K–$40K/month with EDP + Savings Plans (40–60% effective discount) | $30K–$42K/month with EA + Reserved VMs (similar effective discount) |
Benchmarking context:
In observed Vendr transactions, buyers evaluating both AWS and Azure often use competitive pricing as leverage to negotiate 3–8 percentage points better discounts on their preferred platform. Compare AWS and Azure pricing for your workload using Vendr's benchmarking tool.
| Pricing component | Amazon Web Services | Google Cloud Platform |
|---|---|---|
| On-Demand compute (baseline) | t3.medium ~$30/month (Linux, US East) | e2-medium ~$24/month (Linux, us-central1) — ~20% lower list |
| Reserved Instance / Committed Use discount | 30–70% off On-Demand (1- or 3-year commitments) | 37–70% off On-Demand (1- or 3-year Committed Use Discounts) |
| Enterprise discount programs | EDP: 10–35% off total bill | Custom agreements: 10–30% off, often more aggressive for competitive displacements |
| Support costs | Business: 3–10% of spend; Enterprise: $15K/month minimum or 3–10% | Standard: 3% of spend; Enhanced: 5%; Premium: custom, often $15K+/month |
| Estimated total for $50K/month usage | $30K–$40K/month with EDP + Savings Plans | $28K–$38K/month with custom agreement + Committed Use — often 5–10% lower |
Benchmarking context:
Based on Vendr transaction data, buyers who credibly evaluate both AWS and GCP often secure 5–12% better pricing on their chosen platform. See GCP vs. AWS pricing comparisons for your specific workload.
| Pricing component | Amazon Web Services | Oracle Cloud Infrastructure |
|---|---|---|
| On-Demand compute (baseline) | t3.medium ~$30/month (Linux, US East) | VM.Standard.E4.Flex (2 OCPU, 16 GB) ~$50/month — higher list for comparable specs |
| Reserved Instance / Reserved Capacity discount | 30–70% off On-Demand | 22–62% off On-Demand (1- or 3-year Reserved Capacity) |
| Enterprise discount programs | EDP: 10–35% off total bill | UCLA (Universal Credits): 20–50% off for Oracle Database workloads and broader OCI usage |
| Oracle Database licensing | RDS for Oracle: license-included pricing ~$0.40–$2.00+/hour depending on edition | Autonomous Database or BYOL: often 30–50% lower total cost for Oracle-heavy workloads |
| Estimated total for $50K/month usage (Oracle-heavy) | $50K–$70K/month (higher due to Oracle licensing on AWS) | $30K–$45K/month (lower due to Oracle's database pricing advantage) |
Benchmarking context:
In observed Vendr transactions, Oracle-heavy workloads often achieve 30–50% lower total costs on OCI versus AWS, while non-Oracle workloads see minimal pricing advantage. Compare OCI and AWS for your Oracle workloads using Vendr's cost modeling tool.
| Pricing component | Amazon Web Services | IBM Cloud |
|---|---|---|
| On-Demand compute (baseline) | t3.medium ~$30/month (Linux, US East) | bx2-2x8 ~$90/month (Linux, us-south) — significantly higher list |
| Reserved Instance / Reserved Capacity discount | 30–70% off On-Demand | 15–30% off On-Demand (1- or 3-year Reserved Capacity) — smaller discounts |
| Enterprise discount programs | EDP: 10–35% off total bill | Custom agreements: 10–25% off, often tied to broader IBM software commitments |
| Support costs | Business: 3–10% of spend; Enterprise: $15K/month minimum | Advanced: 5% of spend; Premium: custom, often higher than AWS |
| Estimated total for $50K/month usage | $30K–$40K/month with EDP + Savings Plans | $45K–$60K/month — typically 20–40% higher than AWS |
Benchmarking context:
IBM Cloud is typically evaluated for strategic or technical reasons (existing IBM relationships, mainframe connectivity) rather than cost competitiveness. Compare IBM Cloud and AWS if you have specific IBM integration requirements.
AWS offers multiple discount mechanisms depending on your commitment level and spend:
Based on anonymized AWS transactions in Vendr's platform over the past 12 months:
Vendr's dataset shows that buyers who combine EDPs with Savings Plans typically achieve total effective discounts of 40–60% compared to pure On-Demand pricing.
Negotiation guidance: Vendr's AWS discount benchmarking tool shows percentile-based EDP discount rates by annual commitment tier and provides negotiation playbooks for maximizing savings.
Negotiation outcomes depend heavily on your annual spend, growth trajectory, and competitive leverage.
Based on Vendr transaction data from the past 12 months:
Vendr data shows that buyers who negotiate near quarter-end (especially Q4) and present credible competitive alternatives achieve 3–8 percentage points better discounts than those who negotiate mid-quarter without competitive pressure.
Benchmarking context: See what similar companies negotiated for AWS based on percentile benchmarks from Vendr's anonymized transaction database.
An EDP is a custom agreement between your organization and AWS that provides a percentage discount across your entire AWS bill in exchange for a multi-year spending commitment. EDPs are typically available for organizations spending or projecting to spend $100,000+ annually.
Key EDP components:
Based on Vendr's dataset, EDP negotiations typically take 60–90 days from initial discussion to signed agreement. Buyers who start the process 90+ days before their target start date have more leverage and achieve better terms.
Negotiation guidance: Vendr's EDP negotiation playbook provides step-by-step tactics, timing strategies, and discount benchmarks by spend tier.
For most buyers, Savings Plans offer better flexibility than Reserved Instances (RIs) while delivering comparable discounts.
Reserved Instances:
Savings Plans:
Vendr transaction data shows that 60–80% of mid-market and enterprise buyers now prefer Savings Plans over RIs due to flexibility, with RIs reserved for highly predictable, static workloads.
Benchmarking context: Model RI vs. Savings Plan scenarios for your specific usage pattern using Vendr's AWS cost calculator.
Data transfer (egress) fees are one of the most commonly underestimated AWS costs.
Based on AWS's published pricing and Vendr transaction data:
Vendr data shows that buyers who architect for data locality (keeping data and compute in the same region/AZ) and use CloudFront CDN strategically often reduce data transfer costs by 20–40%.
Benchmarking context: Estimate your AWS data transfer costs based on your architecture and usage patterns.
AWS, Azure, and Google Cloud Platform (GCP) have largely converged on list pricing for core services, but discount structures and total cost of ownership differ.
Based on Vendr's comparative transaction data:
Vendr data shows that buyers who credibly evaluate 2–3 cloud platforms and present competitive pricing during negotiations achieve 5–12% better discounts on their chosen platform.
Competitive benchmarks: Compare AWS, Azure, and GCP pricing for your specific workload using Vendr's multi-cloud cost modeling tool.
These are three commitment models that determine how you pay for AWS services:
Most buyers use a mix: Savings Plans or RIs for baseline usage (60–80% coverage) and On-Demand for spikes and experimentation.
Support tier selection depends on your operational maturity, workload criticality, and internal expertise:
Most production deployments require at least Business Support. Enterprise Support is typical for large-scale or mission-critical environments.
Savings Plans are a flexible commitment model that provides discounts (up to 70% off On-Demand) in exchange for committing to a consistent hourly spend (e.g., $5/hour or $50/hour) for 1 or 3 years.
Two types:
Payment options:
All Upfront (highest discount), Partial Upfront, or No Upfront. AWS automatically applies your Savings Plan to eligible usage each hour, with any excess billed at On-Demand rates.
CloudFront is AWS's Content Delivery Network (CDN) that caches and delivers content from edge locations worldwide, reducing latency and data transfer costs.
Pricing components:
CloudFront can reduce total data transfer costs by caching content at edge locations, avoiding repeated egress from your origin (EC2, S3, etc.). For content-heavy applications, CloudFront often pays for itself through reduced origin egress fees.
Cross-region data transfer costs $0.02/GB in most cases. For example, transferring 1 TB of data from US East (N. Virginia) to US West (Oregon) costs approximately $20.
For multi-region architectures (e.g., active-active deployments, disaster recovery, global applications), cross-region transfer can add 5–15% to total costs. Buyers should model these costs during architecture planning and consider data locality strategies to minimize unnecessary transfer.
Trusted Advisor is an automated tool that analyzes your AWS environment and provides recommendations across five categories: cost optimization, performance, security, fault tolerance, and service limits.
Availability:
Trusted Advisor is particularly valuable for identifying cost savings opportunities. Many buyers use it to find quick wins (deleting unused resources, right-sizing instances) before negotiating EDPs.
Based on analysis of anonymized AWS deals in Vendr's dataset, AWS pricing outcomes vary widely depending on commitment structure, negotiation approach, and optimization maturity. Recent data from Vendr shows that buyers who prepare carefully, model their usage accurately, and introduce competitive alternatives often secure meaningfully better pricing—commonly achieving 30–50% total effective discounts compared to On-Demand list pricing through a combination of EDPs, Savings Plans, and architectural optimization.
Key takeaways:
Regardless of platform choice, the most important step is clearly defining requirements, understanding total cost drivers, and benchmarking pricing against comparable deals before committing.
Vendr's AWS pricing and negotiation tools analyze anonymized transaction data to surface percentile-based EDP discount benchmarks, Savings Plan coverage recommendations, and observed negotiation patterns, helping buyers assess how a given AWS quote or renewal compares to recent market outcomes for similar scope and spend levels.
This guide is updated regularly to reflect recent Amazon Web Services pricing and negotiation trends. Consider revisiting it ahead of any new purchase or renewal to account for changing market conditions. Last updated: February 2026.