Newer instance families on AWS aren’t just faster — they’re often cheaper. Graviton-based instances are a good example: AWS prices them lower to drive adoption, and in most benchmarks, they deliver better performance per dollar than their x86 equivalents.

This post breaks down where you can use Graviton (starting with EC2 and RDS), which instance types are available, and what kind of improvements you can realistically expect. If you’re still running older instance families, it’s worth reevaluating.

Graviton-Based Instances (EC2)

Image source: AWS

Today, Graviton is in its 4th generation and AWS offers more than 150 different Graviton-powered Amazon EC2 instance types globally at scale. Most general-purpose and compute-optimized workloads can run on Graviton with minimal changes. Benchmarks consistently show better throughput, lower costs, and up to 60% lower energy consumption compared to x86 instances for compute intensive applications.

Graviton is available across all major EC2 instance categories, such as:

Graviton-based EC2 for compute optimized, memory optimized, high performance computing, etc.

Benchmarks consistently show:

  • Up to 40-60% better price-performance compared to x86 instances
  • Lower energy use
  • Improved throughput and latency

These benefits apply to typical EC2 use cases like web servers, microservices, containers, CI/CD runners, and stateless batch jobs.

You can use AWS Compute Optimizer or nOps to identify EC2 workloads that can migrate to Graviton, test with Arm architecture-based AMIs, and validate performance before switching in production.

Graviton Instances for RDS

If you’re running RDS on older x86-based instances like M5 or R5, switching to Graviton is one of the easiest ways to improve price-performance — and most teams haven’t done it yet. There’s no need to change your database engine or schema. In most cases, you can modify the instance type and immediately start saving.

Graviton is supported for PostgreSQL, MySQL, and MariaDB.

According to AWS benchmarks, Graviton3-based RDS instances deliver up to 27% better price-performance than Graviton2 and handle 29% more queries per second on average — with up to 34% more throughput depending on engine and workload. Latency per dollar also improves by up to 20% for significant cost savings. Building upon these improvements, Graviton4-based RDS instances offer up to a 40% performance enhancement and up to a 29% price/performance improvement over Graviton3-based instances, depending on the database engine, version, and workload.

To get started, modify your RDS instance to a Graviton-based family via the console or IaC. You can use nOps to quickly identify which RDS workloads haven’t yet moved to Graviton and estimate potential savings.

AWS Graviton-Based Instances for Aurora

If you’re using Amazon Aurora and haven’t looked at Graviton-backed instances, you’re likely missing an easy win. Graviton-based Aurora instances (like db.r6g, db.r7g and db.rg8) offer the same availability, backups, and failover setup — with better throughput and lower cost for high performance databases.

In AWS’s own benchmarks, Graviton4-powered Aurora instances deliver faster query execution and lower latency compared to x86, while reducing cost per transaction. These gains are especially noticeable under read-heavy or bursty workloads — which makes it a solid drop-in upgrade for many production clusters.

To get started, modify your Aurora cluster to use a Graviton-based instance type. Use nOps to flag Aurora clusters still running on older x86 families and prioritize high-throughput clusters where the cost savings will be most visible.

Graviton for Lambda

Unlike EC2 or RDS, you don’t choose an instance type for Lambda — but you do choose the CPU architecture. By switching your functions from x86 to Arm64, you can cut costs and achieve optimal performance, especially for compute-heavy or latency-sensitive workloads.

Graviton2-backed Lambdas offer:

  • Up to 34% better price-performance
  • Lower average latency in benchmarks (especially cold starts and CPU-bound tasks)
  • Reduced cost per invocation, thanks to Lambda’s millisecond-level billing granularity

You’ll see the biggest gains on workloads that run frequently or use a lot of memory/CPU — like ETL jobs, image processing, or data transformations.

To get started, update your Lambda’s architecture to Arm64 in the console, AWS CLI, or infrastructure as code. Most interpreted languages (Node.js, Python) and container-based functions will work without changes. Test performance before switching in production, especially if your code includes native binaries or compiled dependencies.

Graviton for ElastiCache & MemoryDB

Graviton is available for Redis and Memcached in ElastiCache, and for Redis in MemoryDB. These workloads are memory-bound and often latency-sensitive — exactly where Graviton shines. Common use cases include caching for web applications, session storage, and low-latency data analytics pipelines.

  • Supported instance types:M6g, R6g, M7g, R7g
  • ElastiCache (Redis):Up to 45% better price-performance
  • MemoryDB:Up to 34% lower cost per transaction

To get started, launch or update your cluster using a Graviton-based node family. No changes to your Redis or Memcached configuration are needed.

Graviton for OpenSearch

OpenSearch (and formerly Elasticsearch) now supports Graviton for both data and master nodes, making it a straightforward cost optimization for search and logging workloads.

  • Supported instance types: M6g, R6g, R6gd, C6g, C7g, M7g, R7g, R7gd
  • Benchmarked benefits:Up to 30% better price-performance on indexing and querying

To migrate, change the instance types for your OpenSearch domain nodes in the console or via CloudFormation.

Graviton for EMR & Fargate

You don’t have to be running web apps to benefit from AWS Graviton-based instances — it also helps behind the scenes.

  • Amazon EMR on EC2 supports M6g, C6g, C7g, and R6g for jobs like Spark, Hive, and Presto, offering up to 30% better price-performance.
  • AWS Fargate now supports Graviton-based compute for ECS and EKS — no instance management required, and you can expect around 20% lower cost per task with comparable performance.

To get started, choose Graviton-based instance families for EMR clusters, or set the platform version and architecture in your Fargate task definition.

How does Graviton pricing work?

AWS Graviton pricing primarily follows the standard AWS pricing model for EC2 instances, which is based on several factors.

Instance Type:

The cost varies depending on the instance family (like M6g, C6g, R6g) and the specific instance size within that family. Each family is optimized for different types of workloads, such as general-purpose, compute-optimized, etc. Other instances are optimized for memory-intensive workloads or storage-intensive workloads.

Usage Time:

Amazon EC2 instances are typically billed by the second, with a minimum of 60 seconds. This means you pay only for the compute time you use.

Region:

AWS Graviton prices can vary by AWS region. For example, instances in North American regions might be priced differently from those in Asia or Europe.

Operating System:

Pricing for AWS Graviton instances varies based on the choice of operating system due to licensing costs, especially for instances running for example Windows compared to those running Linux or other open-source operating systems.

Using additional features like Elastic Block Store (EBS), data transfer, or Elastic IP addresses can add to the costs (these are billed separately).

Purchasing Options for Graviton

There are three models for purchasing Graviton instances:

On-Demand: Pay for what you use without any upfront cost.

Reserved Instances/Savings Plans: Commit to a specific instance type in a region for a term of one or three years, with the option to pay all, some, or none of the cost upfront. This commitment can significantly reduce hourly costs.

Spot Instances: Purchase unused Amazon EC2 capacity at potentially significant discounts compared to the On-Demand price. Spot instance pricing is variable, based on supply and demand, and instances can be interrupted by AWS with a two-minute notification.

Sample On-Demand Pricing: Graviton-Based Instances for compute intensive workloads

Graviton-based instances are fully compatible with Savings Plans and Reserved Instances, and nOps helps ensure you’re getting the most value from both.

With nOps, you get:

  • Graviton Savings: It’s easy to see which workloads can move to Graviton, forecast savings, and track realized results over time with nOps.
  • Right-sizing before you commit: Ensures you’re sizing workloads correctly beforeswitching to Graviton or locking in a commitment — so you’re not just saving on CPU architecture, but also on unused capacity.
  • Commitment Management with a 100% Utilization Guarantee: Intelligently analyze usage patterns and select optimal RI/SP based on workload changes, ensuring you’re always leveraging the best configuration for your needs.

nOps was recently ranked #1 with five stars in G2’s cloud cost management category, and we optimize $2+ billion in cloud spend for our customers.

If you’re migrating to Graviton or already running it, make sure you’re not leaving money on the table. Join our customers using nOps to maximize your commitment savings and leverage automation with complete confidence by booking a demo with one of our AWS experts.