Amazon Redshift adds rg.large and rg.12xlarge instance sizes in AWS GovCloud (US) Regions
AWS has introduced rg.large and rg.12xlarge instance sizes for Amazon Redshift RG instances in AWS GovCloud (US) Regions, expanding compute options for data warehouse and data lake workloads.
Amazon Redshift now supports rg.large and rg.12xlarge instance sizes for RG instances in AWS GovCloud (US-West) and AWS GovCloud (US-East) Regions. These new sizes join existing rg.xlarge and rg.4xlarge options, providing additional flexibility for workload scaling. The instances are designed to handle data warehouse and data lake workloads with improved performance compared to previous generation RA3 instances. Customers can deploy these instances starting with patch version P202 or later.
RG instances include Redshift's vectorized data lake query engine, which processes Apache Iceberg and Parquet data directly on cluster nodes. This allows users to run SQL analytics across both data warehouses and data lakes using a single engine. The new instance sizes maintain compatibility with existing Redshift features, including Elastic Resize and Classic Resize for cluster adjustments. Customers with RA3 clusters can also upgrade to RG instances via Snapshot & Restore.
The rg.large and rg.12xlarge instances are priced competitively, with RG instances offering up to 2.4x faster performance than RA3 instances at a 30% lower price per vCPU. Flexible pricing options are available, including On-Demand, 1-year Reserved Instances, and 3-year Reserved Instances with All Upfront, Partial Upfront, or No Upfront payments. Pricing details are accessible on the Amazon Redshift pricing page.
The expansion of RG instance sizes in AWS GovCloud Regions provides government and public sector customers with enhanced compute options for Amazon Redshift. These instances are tailored for workloads requiring high performance and cost efficiency, particularly in regulated environments. Existing customers can leverage the new sizes to optimize their data analytics infrastructure while maintaining compatibility with existing Redshift features and workflows.