The CFO’s question was direct: “Why are we still paying 40% more for database performance we could get cheaper on Graviton?” The engineering team had been putting off the migration for months, citing complexity and uncertainty about .NET compatibility. But the numbers from AWS’s latest Graviton 4 benchmarks made the conversation impossible to avoid.
In June 2025, AWS released performance data showing Graviton 4-based RDS instances delivering 40% higher performance with 29% better price-performance compared to previous generations. For Aurora PostgreSQL, the gains were even more dramatic: 1.7x higher write throughput and 46% lower commit latency.
This isn’t just another incremental improvement. Graviton 4 represents a fundamental shift in cloud economics that makes migration from a “nice to have” to a financial imperative.
Why Now Is the Time for Graviton Migration
The cloud cost optimization landscape has fundamentally changed. While organizations spent 2023 and early 2024 focused on rightsizing and Reserved Instance optimization, the real savings opportunity has shifted to architecture decisions that seemed too complex to tackle.
Graviton 4’s arrival changes that calculation. The performance gains are substantial enough to justify migration projects that previously lived in engineering backlogs. More importantly, AWS has simplified the migration path for the workloads that matter most: RDS databases, Aurora clusters, and containerized .NET/Java applications.
The financial pressure is real. Organizations running significant database workloads on x86 instances are essentially paying a 29-40% premium for the same performance. In an environment where every percentage point of cloud spend matters, that premium has become impossible to justify.
But here’s what makes 2025 different: the migration complexity that previously blocked these projects has largely disappeared. Modern .NET runs natively on ARM, Java workloads transition seamlessly, and AWS provides benchmarking tools that eliminate guesswork about performance impacts.
Graviton 4 Benchmarks for Amazon RDS: The Numbers That Matter
The June 2025 AWS Database Blog post provided the clearest picture yet of Graviton 4’s impact on RDS workloads. These aren’t marketing projections—they’re benchmarks from real-world database configurations.
Performance Gains That Change Project Justification
Graviton 4-based db.m8g.xlarge instances deliver: – 40% higher performance compared to Graviton 3 – 29% better price-performance ratio – 23% more queries per dollar compared to Graviton 3 – 34% more queries per dollar compared to Graviton 2
These numbers represent the kind of improvement that transforms cost optimization from incremental tweaking to strategic advantage. A database workload that costs $10,000 monthly on Graviton 2 instances could deliver the same performance for $6,600 on Graviton 4—a $40,800 annual saving per workload.
What This Means for Your RDS Strategy
The benchmarks focused on Amazon RDS for PostgreSQL, but the implications extend across database engines. The underlying ARM architecture improvements benefit MySQL, MariaDB, and even SQL Server workloads (though SQL Server requires additional compatibility testing).
Latency improvements translate directly to user experience gains. Applications that previously required aggressive caching to meet response time SLAs can often eliminate that complexity while improving performance. The database layer becomes less of a bottleneck, which often cascades into simplified application architectures.
Query throughput gains mean existing database instances can handle significantly more load before requiring vertical or horizontal scaling. For applications experiencing growth, this effectively delays expensive infrastructure expansion projects.
Aurora PostgreSQL + Graviton 4: Where the Real Gains Live
Aurora PostgreSQL on Graviton 4 represents the most compelling migration target in AWS’s current lineup. The May 2025 benchmarks showed performance improvements that justify prioritizing Aurora migrations over other Graviton projects.
Write Throughput Revolution
R8g Aurora PostgreSQL instances deliver: – 1.7x higher write throughput versus Graviton 2-based R6g instances – 1.38x better price-performance – Up to 46% reduction in commit latency on r8g.16xlarge instances
These improvements compound. Higher write throughput with lower latency means applications can process more transactions per second while providing better user experience. For e-commerce platforms, financial services, or any application where database writes represent a bottleneck, these gains translate directly to business capability.
The Combined Upgrade Strategy
The most dramatic performance gains occur when organizations combine Aurora PostgreSQL version upgrades with Graviton 4 migration. Moving from Aurora PostgreSQL 15.10 on Graviton 2 to version 17.4 on Graviton 4 delivers improvements that exceed the sum of individual upgrades.
This strategy works because: – Aurora PostgreSQL 17.4 includes ARM-optimized query execution – Graviton 4’s memory bandwidth improvements benefit PostgreSQL’s parallel query processing – Combined optimizations reduce lock contention and improve concurrent transaction handling
For organizations running older Aurora PostgreSQL versions, this presents an opportunity to address two upgrade projects simultaneously while capturing maximum performance benefits.
Broader Graviton Cost-Optimization Across AWS
While RDS and Aurora represent the most compelling immediate targets, Graviton 4’s impact extends across AWS services. Understanding the broader cost optimization potential helps prioritize migration efforts and justify larger architectural changes.
EC2 Workload Economics
Industry benchmarks show: – Up to 40% cost reduction for legacy workloads migrated to Graviton 4 (l8g instance types) – 20-40% higher throughput per dollar for general compute workloads – 10-20% lower hourly costs with improved energy efficiency
The 40% cost reduction figure comes from real migration case studies, not theoretical maximums. Organizations achieving these savings typically migrate containerized applications with predictable load patterns and minimal architecture-specific dependencies.
Energy efficiency gains matter more in 2025’s sustainability-focused environment. Organizations with corporate carbon reduction commitments find Graviton’s power efficiency helps meet environmental goals while reducing costs.
Container and Serverless Advantages
Amazon ECS and EKS workloads benefit significantly from Graviton 4’s improved memory bandwidth and CPU performance. Containerized .NET and Java applications often see 15-25% performance improvements with no code changes required.
AWS Lambda functions running on ARM architecture cost approximately 20% less than x86 equivalents while often executing faster. For high-volume serverless workloads, this represents substantial monthly savings with minimal migration effort.
AWS Graviton Savings Dashboard
AWS provides the Graviton Savings Dashboard to eliminate guesswork about potential savings. The tool analyzes your current EC2 and RDS usage patterns and provides estimated cost reductions typically within an hour of configuration.
Dashboard capabilities include: – Instance-level
savings projections – Workload compatibility assessments
– Migration complexity estimates – Cost optimization roadmap
recommendations
This tool transforms Graviton migration from speculation to data-driven decision making. Finance teams can evaluate ROI before committing engineering resources to migration projects.
Practical Migration Plan: .NET/Java Focus
The strategic value of Graviton migration depends on execution quality. Organizations that approach migration systematically capture benefits faster and avoid common pitfalls that delay ROI realization.
Step 1: Audit Current Workloads
Inventory and prioritize based on cost impact: – RDS and Aurora databases → Highest priority (immediate cost savings) – High-traffic .NET Core applications → Second priority (performance + cost gains) – Java microservices and Spring Boot apps → Third priority (easy wins) – Legacy .NET Framework applications → Lower priority (compatibility assessment required)
Document current performance baselines: – Database query response times and throughput – Application response time percentiles – Monthly compute and database costs – Current instance types and utilization patterns
Step 2: Test & Benchmark
Start with non-production environments: – Create parallel Graviton 4 instances (db.m8g.xlarge for RDS testing) – Migrate representative data sets – Run load tests using production traffic patterns – Compare performance metrics against x86 baselines
For .NET applications: – Verify .NET 6+ runtime compatibility (required for ARM support) – Test NuGet package dependencies for ARM compatibility – Validate any native libraries or P/Invoke calls – Benchmark application startup time and steady-state performance
For Java applications: – Confirm JVM version (OpenJDK 11+ recommended for optimal ARM performance) – Test application frameworks (Spring Boot, Quarkus work seamlessly) – Validate any JNI dependencies – Compare garbage collection performance patterns
Step 3: Phased Migration Strategy
Phase 1: Aurora PostgreSQL databases – Migrate non-production Aurora clusters to r8g instances – Upgrade to Aurora PostgreSQL 17.4 simultaneously – Validate application compatibility and performance – Plan production migration windows
Phase 2: Containerized applications – Update ECS task definitions to use ARM-based instance types – Rebuild container images for ARM64 architecture – Deploy to staging environments for validation – Implement blue-green deployment for production migration
Phase 3: EC2-based applications – Migrate .NET Core and Java applications to c7g/m7g instances – Update deployment automation for ARM compatibility – Implement monitoring for performance validation – Plan rollback procedures for rapid recovery
Step 4: Monitor & Validate
Establish success metrics: – Cost reduction: Track monthly compute and database costs – Performance improvement: Monitor application response times and database throughput – Operational stability: Track error rates and availability metrics
Use CloudWatch and application monitoring: – Set up custom dashboards for Graviton-specific metrics – Configure alerts for performance degradation – Implement cost tracking for ROI validation
Step 5: Full Rollout & Optimization
Scale successful migrations: – Apply proven migration patterns to remaining workloads – Update infrastructure-as-code templates for ARM instances – Train operations teams on ARM-specific troubleshooting
Optimize for additional savings: – Implement Reserved Instances for migrated workloads – Consider Savings Plans for flexible capacity planning – Evaluate Spot Instances for development and testing workloads
Leveraging Graviton 4 for FinOps Wins
The most successful Graviton migrations integrate into broader FinOps initiatives rather than operating as isolated engineering projects. This approach accelerates adoption and maximizes financial impact.
Building the Business Case
Quantify immediate opportunities: – Calculate potential annual savings using AWS Graviton Savings Dashboard – Document performance improvements that enable business growth – Identify operational complexity reductions (fewer instances needed)
Address migration investment: – Estimate engineering time required for migration projects – Calculate infrastructure costs during parallel testing phases – Project timeline for ROI realization
Present strategic advantages: – Position ARM migration as future-proofing against continued x86 premium pricing – Highlight sustainability benefits for ESG reporting – Demonstrate technical leadership in cost optimization
Common Migration Pitfalls to Avoid
Underestimating testing requirements: ARM compatibility testing takes longer than expected, especially for applications with native dependencies. Budget additional time for thorough validation.
Ignoring monitoring gaps: Existing monitoring tools may not immediately support ARM instances. Update monitoring configurations before migration to avoid blind spots.
Rushing production deployments: The cost savings potential creates pressure to accelerate migration timelines. Maintain rigorous testing standards to avoid availability impacts.
Overlooking team training: Operations teams need ARM-specific troubleshooting knowledge. Invest in training before production deployments.
The Strategic Reality: Act Now or Pay the Premium
The window for voluntary Graviton migration is closing. As ARM adoption accelerates across the industry, the cost differential between ARM and x86 cloud computing will likely increase. Organizations that delay migration will face growing financial pressure from competitors who captured these efficiency gains earlier.
Financial Impact Timeline: – Immediate: 29-40% cost reduction for migrated workloads – 6-12 months: Cumulative savings fund additional cloud initiatives – 12+ months: Competitive advantage from lower infrastructure costs
Technical Debt Considerations: – Applications designed for x86 architecture accumulate migration complexity over time – New features and dependencies may increase ARM compatibility challenges – Industry momentum toward ARM reduces vendor support for x86-specific optimizations
The data supports immediate action. Graviton 4’s performance improvements are substantial enough to justify migration projects that previously lived in engineering backlogs. The tooling and compatibility ecosystem has matured sufficiently to reduce migration risks to acceptable levels.
Organizations that implement systematic Graviton migration capture immediate cost savings while positioning themselves for continued ARM architecture improvements. Those that delay face growing opportunity costs as cloud economics increasingly favor ARM-based computing.
Your Next Steps: 1. This week: Run AWS Graviton Savings Dashboard analysis for your top 10 workloads 2. This month: Start Aurora PostgreSQL migration pilot with non-production database 3. Next quarter: Implement full migration plan for containerized .NET/Java applications
The question isn’t whether to migrate to Graviton 4—it’s how quickly you can capture the cost and performance advantages before your competition does.
Successful cloud cost optimization requires more than individual service migrations—it demands strategic alignment between engineering capabilities and financial objectives. ZirconTech helps organizations implement comprehensive FinOps strategies that turn infrastructure efficiency into competitive advantage.