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Since 2013, Amazon Redshift has given the complete energy of an information warehouse within the cloud, at a fraction of the on-premises price. Each architectural technology—from dense compute to Amazon RA3 cases, from provisioned to Amazon Redshift Serverless—has made every question cheaper, sooner, and extra environment friendly than the final.
For over a decade, as information volumes have grown and analytics necessities have developed, organizations more and more leverage each information warehouse tables for structured, frequently-accessed information and information lakes for cost-effective storage of numerous datasets. Add AI brokers to the combination they usually question your information warehouse at a scale that dwarfs typical human utilization, resulting in spiraling operational prices.
Amazon Redshift has doubled down on its core strengths to fulfill the calls for of any workload — whether or not pushed by people or AI brokers. For instance, in March 2026, Amazon Redshift improved the efficiency of enterprise intelligence (BI) dashboards and ETL workloads by rushing up new queries by as much as 7 instances. This considerably improves the response instances of low-latency SQL queries, resembling these utilized in near-real-time analytics purposes, BI dashboards, ETL pipelines, and autonomous, goal-seeking AI brokers.
In the present day, we’re saying Amazon Redshift RG cases, a brand new occasion household powered by AWS Graviton. RG cases ship higher efficiency, operating information warehouse workloads as much as 2.2x as quick as RA3 cases at 30% cheaper price per vCPU. Their built-in information lake question engine helps you to run SQL analytics throughout your information warehouse and information lake from a single engine with efficiency as much as 2.4x as quick as RA3 for Apache Iceberg and as much as 1.5x as quick as RA3 for Apache Parquet. This mix of pace, price effectivity, and an built-in information lake question engine makes Redshift RG cases well-suited to deal with the excessive question volumes and low-latency necessities of at this time’s analytics and agentic AI workloads.
You’ll be able to examine new RG cases and present RA3 cases:
| Present RA3 Occasion | Really useful RG occasion | vCPU | Reminiscence (GB) | Main Use Case |
ra3.xlplus |
rg.xlarge |
4 | 32 | Small cluster departmental analytics |
ra3.4xlarge |
rg.4xlarge |
12 → 16 (1.33:1) | 96 GB → 128 GB (1.33:1) | Normal manufacturing workloads, medium information volumes |
This strategy reduces whole analytics prices for patrons operating mixed information warehouse and information lake workloads, whereas simplifying operations by way of a single system for querying each warehouse tables and Amazon Easy Storage Service (Amazon S3) information lakes. We advocate utilizing the AWS Pricing Calculator together with your particular workload patterns to estimate financial savings.
Getting began with Amazon Redshift RG cases
You’ll be able to launch new clusters or migrate present clusters by way of the AWS Administration Console, AWS Command Line Interface (AWS CLI), or AWS API. The built-in information lake question engine is enabled by default.
Within the Amazon Redshift console, you may select new RG cases once you create a cluster.
You’ll be able to migrate previous-generation cases to RG cases with optimum paths primarily based in your cluster configuration to estimate prices, validate compatibility, and automate execution.
- Elastic Resize—in-place migration with 10-Quarter-hour downtime for suitable configurations
- Snapshot and Restore—create a RG cluster from an RA3 snapshot. That is finest for patrons who need to make configuration adjustments throughout the migration
Your exterior tables, schemas, and question syntax—together with present Spectrum queries—stay unchanged. There is no such thing as a have to recreate exterior tables or modify software code. To be taught extra, go to the Redshift Administration Information.
Amazon Redshift now executes information lake queries on cluster nodes—the identical compute that processes information warehouse workloads. Because of this, Amazon Redshift Spectrum is not required. Knowledge lake queries keep inside your VPC boundary, use present IAM roles, and incur zero per-terabyte scanning costs. This removes the $5/TB Spectrum scanning charges that beforehand added to whole Redshift prices.
Now obtainable
Amazon Redshift RG cases are actually obtainable within the following AWS Areas: US East (N. Virginia, Ohio), US West (N. California, Oregon), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Taiwan, Tokyo), Canada (Central), Europe (Frankfurt, Eire, Milan, London, Paris, Spain, Stockholm), and South America (São Paulo). For Regional availability and a future roadmap, go to the AWS Capabilities by Area. For Redshift Provisioned, you may choose On-Demand Situations with hourly billing and no commitments or select Reserved Situations for price financial savings. To be taught extra, go to the Amazon Redshift Pricing web page.
Give RG cases a strive within the Redshift console and ship suggestions to AWS re:Put up for Amazon Redshift or by way of your regular AWS Assist contacts.
— Channy
Up to date 5/12/26: Center East (UAE) faraway from obtainable areas.