Amazon redshift data warehousing6/24/2023 Amazon Redshift delivers on all your SQL analytics needs with up to 5x better price performance than other cloud data warehouses. With native integration into Amazon SageMaker, customers can stay right within their data warehouse and create, train, and build machine learning models in SQL. Redshift is also integrated with AWS Data Exchange enabling users to find, subscribe to, and query third party datasets and combine with their data for comprehensive insights. Redshift enables streamlined data ingestion with no-code, automated data pipelines that ingest streaming data or Amazon S3 files automatically. Amazon Redshift enables analytics on all your data with deep integration into database services with features like Amazon Aurora Zero-ETL to Amazon Redshift and federated querying to access data in place from operational databases like Amazon RDS and your Amazon S3 data lake. With Redshift Spectrum, Amazon Redshift manages all the computing infrastructure, load balancing, planning, scheduling, and execution of your queries on data stored in Amazon S3. Amazon Redshift also has automatic tuning capabilities, and surfaces recommendations for managing your warehouse in Redshift Advisor. Amazon Redshift Serverless automatically provisions and scales the data warehouse capacity to deliver high performance for demanding and unpredictable workloads, and you pay only for the resources you use. AWS manages the work needed to set up, operate, and scale a data warehouse on your behalf, freeing you to focus on building your applications. Q: How does Amazon Redshift simplify data warehouse and analytics management?Īmazon Redshift is fully managed by AWS so you no longer need to worry about data warehouse management tasks such as hardware provisioning, software patching, setup, configuration, monitoring nodes and drives to recover from failures, or backups. Amazon Redshift supports industry-leading security with built-in identity management and federation for single sign-on (SSO), multi-factor authentication, column-level access control, row-level security, role-based access control, Amazon Virtual Private Cloud (Amazon VPC), and faster cluster resize. Amazon Redshift lets you get insights from running real-time and predictive analytics on all your data across your operational databases, data lake, data warehouse, streaming data, and third-party datasets. Performance innovations are available to customers at no additional cost. With tens of thousands of customers running analytics on terabytes to petabytes of data, Amazon Redshift optimizes real-world customer workload performance, based on fleet performance telemetry, and delivers performance that scales linearly to the workload, while keeping costs low. Amazon Redshift offers leading price performance for diverse analytics workloads, whether it is dashboarding, application development, data sharing, ETL (Extract, Transform, Load) jobs or several others. Amazon Redshift Serverless automatically provisions and scales data warehouse capacity to deliver high performance for demanding and unpredictable workloads. Thousands of customers choose Amazon Redshift to accelerate their time to insights because it is a powerful analytics system that integrates well with database and machine learning services, is streamlined to use, and can become a central service to deliver on all their analytics needs. Q: What are the top reasons customers choose Amazon Redshift? With its Massively Parallel Processing (MPP) engine and architecture that separates compute and storage for efficient scaling, and machine learning driven performance innovations (for example: AutoMaterialized Views), Amazon Redshift is built for scale and delivers up to 5x better price performance than other cloud data warehouses. Amazon Redshift Serverless enables your engineers, developers, data scientists, and analysts to get started easily and scale analytics quickly in a zero-administration environment. Amazon Redshift is deeply integrated with AWS database, analytics, and machine learning services to employ Zero-ETL approaches or help you access data in place for near real-time analytics, build machine learning models in SQL, and enable Apache Spark analytics using data in Redshift. Whether your growing data is stored in operational data stores, data lakes, streaming data services or third-party datasets, Amazon Redshift helps you securely access, combine, and share data with minimal movement or copying. Tens of thousands of customers use Amazon Redshift every day to run SQL analytics in the cloud, processing exabytes of data for business insights.
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