Key Features of Oracle Autonomous AI Database

Provides information on key features of Autonomous AI Database, an affordable, feature-rich service in the cloud.

Key Features

• Managed: Oracle simplifies end-to-end management of the database:

  • Provisioning new databases

  • Growing or shrinking storage and compute resources

  • Patching and upgrades

  • Backup and recovery

• Fully elastic scaling: Scale compute and storage independently to fit your database workload with no downtime:

  • Size the database to the exact compute and storage required

  • Scale the database on demand: Independently scale compute or storage

  • Shut off idle compute to save money

• Auto scaling: Allows your database to use more CPU and IO resources or to use additional storage automatically when the workload or storage demand requires additional resources:

  • Specify the number of CPUs for your Autonomous AI Database workload.

  • Use compute auto scaling to allow the database to use up to three times more CPU and IO resources, depending on workload requirements. Compute auto scaling is enabled by default when you create an Autonomous AI Database.

  • Use storage auto scaling to allow the database to expand to use up to three times the reserved base storage, depending on your storage requirements. Storage auto scaling is disabled by default when you create an Autonomous AI Database.

  • Manage auto scaling from the Oracle Cloud Infrastructure Console to enable or disable compute auto scaling or storage auto scaling for your Autonomous AI Database.

• Autonomous AI Database supports:

  • Existing applications, running in the cloud or on premises

  • Connectivity via SQL*Net, JDBC, ODBC

    See Connect to Autonomous AI Database for more information.

  • Third-party data-integration tools

  • Oracle cloud services: Oracle Analytics Cloud, Oracle GoldenGate Marketplace, and others

• High-performance queries and concurrent workloads: Optimized query performance with preconfigured resource profiles for different types of users.

• Oracle SQL: Autonomous AI Database is compatible with existing applications that support Oracle AI Database.

• Built-in web-based data analysis tool: Web-based notebook tool for designing and sharing SQL based data-driven, interactive documents.

• Database migration utility: Easily migrate from MySQL, Amazon AWS Redshift, PostgreSQL, SQL Server, and other databases.

Simple Cloud-based Data Loading

Autonomous AI Database provides:

• Fast, scalable data-loading from Oracle Cloud Infrastructure Object Storage, Azure Blob Storage or Azure Data Lake Storage, Amazon S3, Amazon S3-Compatible, GitHub Repository, Google Cloud Storage, or on-premises data sources.

Oracle Database Actions

Database Actions is a web-based interface that uses Oracle REST Data Services to provide development, data tools, and administration and monitoring features for Autonomous AI Database, including the following:

• Development Tools

  • SQL Navigator and Worksheet: view objects and enter and run SQL and PL/SQL statements, and create database objects

  • Data Modeler: provides an integrated version of Oracle SQL Developer Data Modeler with basic reporting features. You can create diagrams from existing schemas, retrieve data dictionary information, generate DDL statements, and export diagrams

  • REST: An IDE for your REST APIs that enables you to manage templates, handlers and OAuth clients, generate API documentation, and test APIs.

  • LIQUIBASE: View ChangeLogs applied to your schema.

  • JSON: Create collections, upload documents, query and filter your data, create diagrams for your JSON document structures, and create relational views and indexes.

  • Charts: Use SQL queries to build rich charts and dashboards containing multiple charts.

  • Scheduling: An interface for DBMS_SCHEDULER that enables you to monitor jobs, view execution history, forecast upcoming jobs, and visualize scheduler chains.

  • Oracle Machine Learning: provides several components accessible through a common user interface. OML Notebooks supports Python, R, SQL, PL/SQL, and Markdown interpreters, with access to in-database ML through OML4Py, OML4R, and OML4SQL. OML Models supports managing and deploying in-database models. OML AutoML UI provides a no-code user interface to build, evaluate, and deploy in-database models using automated machine learning.

  • Oracle APEX: Log in to Oracle APEX, develop and run rich, low-code web applications.

  • Graph Studio: Oracle Graph Studio lets you create property graph databases and automates the creation of graph models and in-memory graphs from database tables.

  • Spatial Studio: Oracle Spatial Studio is a web-based interface that enables you to explore, visualize, and analyze geospatial data on your Autonomous AI Database Serverless instance.

• Data Studio

  • Data Load: load or access data from local files or remote databases.

  • Catalog: understand data dependencies and the impact of changes.

  • Data Insights: discover anomalies, outliers and hidden patterns in your data.

  • Data Analysis: analyze your data

  • Data Transforms: transform data for analysis and other applications.

• Administration and Monitoring

  • Manage users

  • Database Dashboard: Monitor database activity charts such as CPU usage, number of executing SQL statements, and wait events formerly found on your Autonomous AI Database Service Console.

  • Performance Hub: Access SQL Monitoring reports and Active Session History (ASH) Analytics.

Disaster Recovery Options

Autonomous Data Guard Autonomous AI Database provides Oracle Autonomous Data Guard to enable a standby (peer) database to provide data protection and disaster recovery for your Autonomous AI Database instance. When you add an Oracle Autonomous Data Guard standby database, the system creates a standby database that continuously gets updated with the changes from the primary database. You can use Autonomous Data Guard with a standby in the current region, a local standby, or with a standby in a different region, a cross region standby. You can also use Oracle Autonomous Data Guard with both a local standby and a cross region standby.

Backup-Based Disaster Recovery uses backups to instantiate a peer database at the time of switchover or failover. This enables you to have a lower cost and higher Recovery Time Objective (RTO) disaster recovery option for your Autonomous AI Database, as compared with Oracle Autonomous Data Guard. For local backup-based disaster recovery, existing local backups are utilized. There are no additional costs for a local Backup-Based Disaster Recovery. cross region Backup-Based Disaster Recovery incurs an additional cost.

SQL Developer Support

Using Autonomous AI Database with SQL Developer you can do the following:

• Connect to Autonomous AI Database

• Create tables, indexes, and materialized views in Autonomous AI Database

• Load data into an Autonomous AI Database

• Copy tables to Autonomous AI Database

• Transfer a schema to Autonomous AI Database

Business Intelligence Tools Support

Autonomous AI Database is compatible with a number of business intelligence and data visualization tools from Oracle and from trusted third parties:

• Oracle Analytics Cloud

• Oracle Analytics Desktop

• Third-party Business Intelligence tools