Introduction: A New Era for Cloud Data Warehousing
Since its launch in 2013, Amazon Redshift has been at the forefront of cloud data warehousing, delivering enterprise-grade performance at a fraction of on-premises costs. Over the years, each architectural leap—from dense compute nodes to Amazon RA3 instances, from provisioned clusters to Amazon Redshift Serverless—has made queries cheaper, faster, and more efficient. Now, as data volumes surge and analytics demands evolve, organizations rely on both structured warehouse tables for frequently accessed data and data lakes for cost-effective storage of diverse datasets. The rise of AI agents, which can query data warehouses at scales far beyond typical human usage, adds further pressure on operational costs. To address these challenges, Amazon Redshift is doubling down on innovation. In March 2026, it already improved BI dashboard and ETL performance by up to 7× for new queries. Today, we are announcing Amazon Redshift RG instances, a new instance family powered by AWS Graviton processors, designed to meet the high query volumes and low-latency requirements of modern analytics and agentic AI workloads.
Next-Generation Performance with AWS Graviton
The new RG instances leverage AWS Graviton processors, which are custom-built by AWS using Arm-based architecture. Compared to the previous RA3 instances, RG instances deliver up to 2.2× faster performance for data warehouse workloads while reducing price per vCPU by 30%. This means organizations can handle larger queries, support more concurrent users, and lower their total cost of ownership—all without sacrificing speed. For workloads driven by human analysts or autonomous AI agents, the performance improvements translate into faster insights and lower operational overhead.
Integrated Data Lake Query Engine
A standout feature of RG instances is the integrated data lake query engine. This engine allows you to run SQL analytics across both your data warehouse tables and your data in Amazon Simple Storage Service (Amazon S3) using a single, unified system. Performance benchmarks show that for Apache Iceberg tables, RG instances can be up to 2.4× faster than RA3 instances, and for Apache Parquet, up to 1.5× faster. This integration simplifies operations by eliminating the need to manage separate query engines for your data warehouse and data lake. Whether you are analyzing structured BI data or semi-structured logs stored in S3, you can do it all from one place, reducing both complexity and cost.
Comparing RG and RA3 Instances
To help you understand the differences, here is a comparison of current RA3 instances and the recommended RG equivalents:
| Current RA3 Instance | Recommended RG Instance | vCPU | Memory (GB) | Primary Use Case |
|---|---|---|---|---|
| ra3.xlplus | rg.xlarge | 4 | 32 | Small cluster departmental analytics |
| ra3.4xlarge | rg.4xlarge | 12 → 16 (1.33:1) | 96 → 128 (1.33:1) | Standard production workloads, medium data volumes |
This migration path provides a straightforward upgrade: more vCPUs and memory per instance at a lower cost per vCPU. For tailored savings estimates, we recommend using the AWS Pricing Calculator with your specific workload patterns.
Getting Started with Amazon Redshift RG Instances
Launching RG instances is simple. You can create new clusters or migrate existing ones using the AWS Management Console, AWS Command Line Interface (AWS CLI), or AWS API. The integrated data lake query engine is enabled by default, so you can start querying across warehouse tables and S3 data lakes immediately. No additional configuration is required. For step-by-step guidance, refer to the Amazon Redshift documentation.
Conclusion
With Amazon Redshift RG instances, AWS continues its tradition of pushing the boundaries of cloud analytics. By combining Graviton processors with an integrated data lake query engine, RG instances deliver up to 2.2× faster performance and 30% lower price per vCPU compared to RA3 instances. This makes them ideal for handling the high query volumes and low-latency requirements of today’s analytics and agentic AI workloads. Whether you are modernizing your data warehouse or building a unified analytics platform, RG instances offer a compelling balance of speed, cost efficiency, and simplicity. Start exploring today to see how they can transform your data operations.