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Amazon Redshift Serverless

Get insights from data in seconds without having to manage data warehouse infrastructure

Benefits of Amazon Redshift Serverless

Focus on obtaining insights by getting starting quickly and running real-time or predictive analytics on all your data without worrying about managing data warehouse infrastructure.
Intelligent, proactive, and automatic scaling for dynamic workloads is enabled along dimensions like query complexity, frequency, ETL, or dashboarding usage patterns to deliver tailored performance optimizations.
Pay only for what you use on a per-second basis, and pay nothing when the data warehouse is idle. Adjust your desired price-performance targets for your workload to maintain consistent performance and stay on budget.

Why Amazon Redshift Serverless?

Easily run analytics workloads of any size without managing data warehouse infrastructure. Developers, data scientists, and data analysts can work across data warehouses and data lakes to build reporting and dashboarding applications, perform real-time analytics, collaborate on data, and build and train machine learning (ML) models. You pay only for what you use, so you save on costs. Amazon Redshift Serverless offers flexibility to support a diverse set of workloads of varying complexity, starting at a low price point. The new AI-driven scaling and optimization technology enables Amazon Redshift Serverless to automatically and proactively provision and scale data warehouse capacity, delivering fast performance for even the most demanding workloads. The system uses AI techniques to learn customer workload patterns across key dimensions, such as concurrent queries, query complexity, influx of data volume, and ETL patterns. It then continually adjusts resources throughout the day and applies tailored performance optimizations. These holistic and AI-enhanced techniques provide the best optimization for a given workload. You can set a desired price-performance target, and the data warehouse automatically scales to meet it. Load data and start querying right away in an easy-to-use, zero administration environment.

Use cases

Perform what-if analyses, anomaly detection, and ML-based forecasting, and get fast, actionable insights from your data.

No longer spend time determining compute capacity and encountering overspending or underserving as you run workloads with regular usage throughout the day and peaks of activity that involve complex, hard-to-predict queries.

Unsure of how to size your data warehouse when deploying a new data-driven application? Start an Amazon Redshift Serverless endpoint, and your data warehouse will be sized according to your workload requirements.

Have applications with high variability in usage? Think of your HR, budgeting, and operational reporting applications. You no longer have to over- or under-provision capacity. Avoid overpaying, performance issues, and poor user experiences.

For multi-tenant applications with each tenant having specific busy and idle periods—depending on the time of day, year, promotional events, and so on—architect to use a workgroup for each tenant with a wide capacity range. Any workgroup can quickly scale up to handle periods of high activity.