Customers who want to use graph analytics need a separate specialty database, data scientists who want to use ML must export data to and reimport it from another AWS service, and data ingestion and transformation require separate AWS or third-party services. For instance, organizations must pay for and integrate Lambda, Kinesis, and S3 just to move data from Amazon Aurora to Redshift-or master Amazon Glue, which requires a DBA to define the ETL job whereupon Glue generates PySpark code, which often needs to be customized based on validation and transformation requirements. Customers can easily create self-service data marts using built-in capabilities for data ingest, transformation, ML, business analytics, graph analytics, geospatial analytics, and application development.Īmazon Redshift is missing an extensive set of data and analytical capabilities that are included in Autonomous Data Warehouse. Finally, Oracle makes it easy for customers to comply with data residency requirements.Ĭan customers build a self-service data mart for reporting without having to integrate multiple additional services?Īutonomous Data Warehouse includes comprehensive capabilities to address a broad set of analytical use cases.Fourth, Autonomous Data Warehouse reduces risk with production-hardened data security and privacy.Third, Autonomous Data Warehouse delivers consistent performance as workloads change by automatically scaling resources and tuning the database.Second, Autonomous Data Warehouse provides high availability with zero downtime for scaling or maintenance.First, only Autonomous Data Warehouse lowers total cost of ownership with built-in capabilities that eliminate the need for multiple single-purpose, add-on services that require integration.It’s available in both the Oracle Cloud Infrastructure (OCI) and customers’ data centers with Oracle choose Oracle over Amazon Redshift for several reasons: It includes tools for self-service data loading, data transformations, business models, automatic insights, and built-in converged database capabilities that enable simpler queries across multiple data types and machine learning analysis. It automates provisioning, configuring, securing, tuning, scaling, patching, backing up, and repairing of the data warehouse. Customers choose Oracle Autonomous Data Warehouse vs Amazon Redshift, a cloud data warehouse service that eliminates all the complexities of operating a data warehouse, securing data, and developing data-driven applications.
0 kommentar(er)
