Estimate Amazon Redshift costs for Serverless RPU and provisioned nodes with Managed Storage, Spectrum, and Concurrency Scaling.
$0.375 per RPU-hour. Billed per second (min 60s per query).
Average hours per day that RPUs are actively processing queries.
$0.024 per GB-month for Redshift Managed Storage (RMS).
$5.00 per TB scanned from S3 via Redshift Spectrum.
Serverless automatically scales compute in RPU (Redshift Processing Units) and bills per second of active usage. Ideal for variable or unpredictable workloads. Provisioned clusters run 24/7 with fixed node capacity, offering better cost efficiency for steady-state workloads with Reserved pricing discounts up to 50%.
dc2 nodes use local SSD storage and are best for datasets under ~2 TB per node. ra3 nodes decouple compute from storage using Redshift Managed Storage (RMS) backed by S3, allowing you to scale storage independently. ra3 is recommended for most new clusters.
Redshift Spectrum lets you query data directly in S3 without loading it into Redshift. Charged at $5 per TB of data scanned. Use columnar formats (Parquet, ORC) and partitioning to minimize scan costs. Great for extending your warehouse to a data lake architecture.
Concurrency Scaling adds transient clusters to handle burst read queries. Each cluster gets 1 free hour per day of concurrency scaling credit. Beyond that, you pay the same per-second rate as your main cluster. Credits accumulate over 30 days, providing up to 30 free hours of scaling per month.
Output will appear here...The Redshift Cost Estimator projects your monthly Amazon Redshift bill for both Serverless and provisioned deployment models. For Serverless, configure your base RPU capacity and expected query hours to see RPU-hour charges alongside Managed Storage costs. For provisioned clusters, select node types (RA3, DC2, or DS2), node counts, and Reserved Instance terms. The estimator also covers Redshift Spectrum charges for querying external S3 data and Concurrency Scaling costs for burst capacity. Use it to model different configurations and find the price-performance sweet spot for your data warehouse workload.
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