Oracle Autonomous Database provides an easy-to-use, fully autonomous database that scales elastically and delivers fast query performance. As a service, Autonomous Database does not require database administration.
With Autonomous Database you do not need to configure or manage any hardware or install any software. Autonomous Database handles provisioning the database, backing up the database, patching and upgrading the database, and growing or shrinking the database. Autonomous Database is a completely elastic service.
At any time you can scale, increase or decrease, either the compute or the storage capacity. When you make resource changes for your Autonomous Database instance, the resources automatically shrink or grow without requiring any downtime or service interruptions.
Autonomous Database is built upon Oracle Database, so that the applications and tools that support Oracle Database also support Autonomous Database. These tools and applications connect to Autonomous Database using standard SQL*Net connections. The tools and applications can either be in your data center or in a public cloud. Oracle Analytics Cloud and other Oracle Cloud services provide support for Autonomous Database connections.
Autonomous Database also includes the following:
Oracle APEX (APEX): a low-code development platform that enables you to build scalable, secure enterprise apps with world-class features.
Oracle REST Data Services (ORDS): a Java Enterprise Edition based data service that makes it easy to develop modern REST interfaces for relational data and JSON Document Store.
Database Actions: is a web-based interface that uses Oracle REST Data Services to provide development, data tools, administration, and monitoring features for Autonomous Database.
Oracle Machine Learning Notebooks Early Adopter is an enhanced web-based notebook platform for data engineers, data analysts, R and Python users, and data scientists. You can write code, text, create visualizations, and perform data analytics including machine learning. In Oracle Machine Learning, notebooks are available in a project within a workspace, where you can create, edit, delete, copy, move, and even save notebooks as templates.