About Autonomous AI Database

Oracle Autonomous AI Database on Dedicated Exadata Infrastructure is a highly automated, fully managed database environment running in Oracle Cloud Infrastructure (OCI) with committed hardware and software resources. These isolated resources enable organizations to meet stringent security, availability, and performance requirements while reducing cost and complexity. Autonomous AI Databases are provisioned inside an Autonomous Container Database (ACD) and are user databases. You can create many Autonomous AI Databases in a single Autonomous Container Database resource. On Oracle Public Cloud and Exadata Cloud@Customer deployments, an Autonomous AI Database will inherit the retention lock settings and associated backup rules from its parent ACD.

To get a holistic idea of the four layer architecture used with Autonomous AI Database on Dedicated Exadata Infrastructure and understand Autonomous AI Database's positioning in this architecture, refer to Components of Autonomous AI Database on Dedicated Exadata Infrastructure.

Application DBAs create, monitor and manage Autonomous AI Databases. Additionally, they create and manage Oracle Database users within these databases, and provide others the information necessary access the database. You can connect to your Autonomous AI Database and start developing database applications after your fleet administrator sets up infrastructure resources and an Application DBA provisions an Autonomous AI Database with database users. A database user can also connect to Autonomous AI Database using various tools such as SQL*Plus, SQLcl, Database Actions, or Oracle APEX.

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Autonomous AI Database Requirements

Resource Requirements

To provision an Autonomous AI Database, you need an Autonomous Container Database with or without Autonomous Data Guard, depending on disaster recovery requirements. See Create an Autonomous Container Database for details.

Required IAM Policies

You must have an Oracle Cloud Infrastructure account with privileges granted through required IAM Policies. The required policies depend on the operation you are performing. For a list of IAM policies pertaining to Autonomous AI Databases, see Policies to Manage Autonomous AI Databases.

Database Features Managed from Autonomous AI Database

The following features can be defined and managed at the Autonomous AI Database level.

Feature	Notes	Further Reference
Workload Type You can configure your database to be one of either Autonomous AI Lakehouse or Autonomous AI Transaction Processing workload types.	Oracle Autonomous AI Lakehouse is a cloud data warehouse service that eliminates virtually all the complexities of operating a data warehouse, securing data, and developing data-driven applications. Oracle Autonomous AI Transaction Processing is a fully automated database service optimized to run transactional, analytical, and batch workloads concurrently.	About Autonomous AI Database on Dedicated Exadata Infrastructure
View Connection Details You can download client credentials and view the TNS names and connection strings of an Autonomous AI Database from the Oracle Cloud Infrastructure (OCI) console.	Oracle client credentials (wallet files) are downloaded from Autonomous AI Database by a service administrator. If you are not an Autonomous AI Database administrator, your administrator should provide you with the client credentials. For cross-region standby Autonomous AI Databases, you can download region-specific connection strings.	About Connecting to a Dedicated Autonomous AI Database
Autonomous AI Database for Developers You can create an Autonomous AI Database for Developers instance. Autonomous AI Database for Developers is a free tier offering designed for database development and functional testing activities.	Autonomous AI Database for Developers comes fixed at 4 ECPUs and 32GB storage, and do not support manual or auto-scaling. As developer database instances can only be created on an ECPU-based ACDs without Autonomous Data Guard, the Free instance toggle button is disabled for ACDs with OCPU, Autonomous Data Guard, or both.	Autonomous AI Database for Developers
CPU Count You can select the number of CPUs for your database from the list of provisionable CPUs.	The CPU type, that is, ECPU or OCPU is determined by the parent Autonomous Exadata VM Cluster's compute type. This value defaults to 2 ECPUs or 1 OCPU depending on the CPU type.	Compute Management in Autonomous AI Database
CPU Auto Scaling CPU auto scaling permits Autonomous AI Database to automatically use up to three times as many CPUs as specified by CPU Count as the workload on the database increases.	You can enable CPU Auto Scaling while provisioning an Autonomous AI Database or after one has already been provisioned.	Enable or Disable Auto Scaling of an Autonomous AI Database
Storage You can specify the storage to allocate to your database in terabytes (GB) while provisioning an Autonomous AI Database.	The minimum value is 32 GB. The default values are 1024 GB for Autonomous AI Lakehouse and 32 GB for the Autonomous AI Transaction Processingworkloads.
Elastic Pool Elastic pools help you improve operating efficiency and reduce costs by bringing all of your databases to the cloud. This also supports consolidating resources and simplifying administration and operations by using Autonomous AI Database.	With Compute auto scaling disabled, you can choose to create an elastic pool as a pool leader or join an existing elastic pool as a pool member using: The elastic pool options under the Configure the database section, while: Provisioning a new Autonomous AI Database Cloning an Autonomous AI Database or its backup The elastic pool options on the Manage resource allocation dialog from the Autonomous AI Database Details page.	Only Autonomous AI Transaction Processing databases without Autonomous Data Guard that use ECPU compute model can be used to create an elastic pool.
Database Authentication You set the database username and password while provisioning a database.	The user name and password is defined while creating the database will be the ADMIN username and password. An Application DBA can connect to this database using the ADMIN username and password to create other Database users.	Create Database Users
Access Control You can configure network access by creating an access control list (ACL). An ACL provides additional protection to your Autonomous AI Database by allowing only the client with specific IP addresses to connect to the database. If the parent Autonomous Container Database uses Autonomous Data Guard, you can define access control for the standby database also.	Depending on the types of addresses in your list, you can choose one of the following IP notation type options: IP Address: Specify individual IP addresses. CIDR Block: Specify ranges of public IP addresses using CIDR notation.	Access Control Within Autonomous AI Database on Dedicated Exadata Infrastructure
Contact Email You can provide contact emails where you can receive operational notifications, announcements, and unplanned maintenance notifications regarding your Autonomous AI Database.	Oracle recommends using the email address of an administrator group rather than an individual's, whenever possible, to ensure no important notifications or announcements are missed.
Character Set Autonomous AI Database lets you choose a character set of your choice from a list of supported character sets while provisioning an Autonomous AI Database.	You choose a Character Set and National Character Set while provisioning an Autonomous AI Database. The list of supported character sets currently includes all database character sets supported on ASCII-based platforms.	Character Set Selection for Autonomous AI Database
Database In-Memory You can enable Database In-memory for your Autonomous AI Database by allocating a percentage of its System Global Area (SGA) to the In-Memory column store (IM column store) either while provisioning the database or later. The In-Memory Column Store (IM column store) is the key feature of Database In-Memory. The IM column store maintains copies of tables, partitions, and individual columns in a special compressed columnar format optimized for rapid scans.	You can enable or disable Database In-Memory for an existing Autonomous AI Database from its Details page on the Oracle Cloud Infrastructure (OCI) console. You can also enable Database In-Memory on databases cloned from a database instance or backup, irrespective of whether the clone source has Database In-memory enabled.	Database In-Memory
Database Cloning You can clone an Autonomous AI Database, creating a point-in-time copy of it or its backup set. You can use the cloning feature to quickly set up an Autonomous AI Database with historical data for purposes such as testing, development, or analytics.	Autonomous AI Database supports the following clone types: Full Clone: A full clone creates a new database that includes the metadata and data from the source database. Metadata Clone: This clone type creates a new database that includes all source database schema metadata, but not the source database data.	About Cloning Autonomous AI Database on Dedicated Exadata Infrastructure
Ops Insights Ops Insights is a cloud-native service that provides 360-degree insight into the resource utilization and capacity of databases and hosts. You can easily analyze CPU and storage resources, forecast capacity issues, and proactively identify SQL performance issues across your database fleet.	By default, Ops Insights is disabled for an Autonomous AI Database, and you must enable it from the Oracle Cloud Infrastructure console. With Ops Insights, you can: Analyze resource usage of databases/hosts across the enterprise. Forecast future demand for resources based on historical trends. Compare SQL Performance across databases and identify common patterns. Identify SQL performance trends across enterprise-wide databases. Analyze AWR statistics for database performance, diagnostics, and tuning across a fleet of databases.	Use Operations Insights on Autonomous AI Database on Dedicated Exadata Infrastructure Get Started with Ops Insights
Autonomous AI Database Metrics You can monitor the health, capacity, and performance of your Autonomous AI Databases with metrics, alarms, and notifications. The Autonomous AI Database metrics help you measure useful quantitative data, such as CPU and storage utilization, the number of successful and failed database logon and connection attempts, database operations, SQL queries, and transactions, and so on. You can use metrics data to diagnose and troubleshoot problems with your Autonomous AI Database resources.	You can use Oracle Cloud Infrastructure console or Monitoring APIs to view metrics.	Monitor Databases with Autonomous AI Database Metrics
Data Safe Oracle Data Safe helps you understand the sensitivity of your data, evaluate risks to data, mask sensitive data, implement and monitor security controls, assess user security, monitor user activity, and address data security compliance requirements in your databases.	Oracle Data Safe provides the following set of features in a single, easy-to-use management console: Security Assessment helps you assess the security of your database configuration. User Assessment helps you assess the security of your database users and identify high risk users. Data Discovery helps you find sensitive data in your database. Data Masking provides a way for you to mask sensitive data so that the data is safe for non-production purposes. Activity Auditing lets you audit user activity on your database so you can monitor database usage and be alerted of unusual database activities. Before you can register your database with Data Safe, Data Safe must be configured to access databases in your dedicated infrastructure configuration.	Oracle Data Safe Overview

Feature

Notes

Further Reference

Workload Type

You can configure your database to be one of either Autonomous AI Lakehouse or Autonomous AI Transaction Processing workload types.

Oracle Autonomous AI Lakehouse is a cloud data warehouse service that eliminates virtually all the complexities of operating a data warehouse, securing data, and developing data-driven applications.

Oracle Autonomous AI Transaction Processing is a fully automated database service optimized to run transactional, analytical, and batch workloads concurrently.

About Autonomous AI Database on Dedicated Exadata Infrastructure

View Connection Details

You can download client credentials and view the TNS names and connection strings of an Autonomous AI Database from the Oracle Cloud Infrastructure (OCI) console.

Oracle client credentials (wallet files) are downloaded from Autonomous AI Database by a service administrator. If you are not an Autonomous AI Database administrator, your administrator should provide you with the client credentials.

For cross-region standby Autonomous AI Databases, you can download region-specific connection strings.

About Connecting to a Dedicated Autonomous AI Database

Autonomous AI Database for Developers

You can create an Autonomous AI Database for Developers instance. Autonomous AI Database for Developers is a free tier offering designed for database development and functional testing activities.

Autonomous AI Database for Developers comes fixed at 4 ECPUs and 32GB storage, and do not support manual or auto-scaling.

As developer database instances can only be created on an ECPU-based ACDs without Autonomous Data Guard, the Free instance toggle button is disabled for ACDs with OCPU, Autonomous Data Guard, or both.

Autonomous AI Database for Developers

CPU Count

You can select the number of CPUs for your database from the list of provisionable CPUs.

The CPU type, that is, ECPU or OCPU is determined by the parent Autonomous Exadata VM Cluster's compute type. This value defaults to 2 ECPUs or 1 OCPU depending on the CPU type.

Compute Management in Autonomous AI Database

CPU Auto Scaling

CPU auto scaling permits Autonomous AI Database to automatically use up to three times as many CPUs as specified by CPU Count as the workload on the database increases.

You can enable CPU Auto Scaling while provisioning an Autonomous AI Database or after one has already been provisioned.

Enable or Disable Auto Scaling of an Autonomous AI Database

Storage

You can specify the storage to allocate to your database in terabytes (GB) while provisioning an Autonomous AI Database.

The minimum value is 32 GB.

The default values are 1024 GB for Autonomous AI Lakehouse and 32 GB for the Autonomous AI Transaction Processingworkloads.

Elastic Pool

Elastic pools help you improve operating efficiency and reduce costs by bringing all of your databases to the cloud. This also supports consolidating resources and simplifying administration and operations by using Autonomous AI Database.

With Compute auto scaling disabled, you can choose to create an elastic pool as a pool leader or join an existing elastic pool as a pool member using:

The elastic pool options under the Configure the database section, while:
- Provisioning a new Autonomous AI Database
- Cloning an Autonomous AI Database or its backup
The elastic pool options on the Manage resource allocation dialog from the Autonomous AI Database Details page.

Only Autonomous AI Transaction Processing databases without Autonomous Data Guard that use ECPU compute model can be used to create an elastic pool.

Database Authentication

You set the database username and password while provisioning a database.

The user name and password is defined while creating the database will be the ADMIN username and password. An Application DBA can connect to this database using the ADMIN username and password to create other Database users.

Create Database Users

Access Control

You can configure network access by creating an access control list (ACL). An ACL provides additional protection to your Autonomous AI Database by allowing only the client with specific IP addresses to connect to the database.

If the parent Autonomous Container Database uses Autonomous Data Guard, you can define access control for the standby database also.

Depending on the types of addresses in your list, you can choose one of the following IP notation type options:

IP Address: Specify individual IP addresses.
CIDR Block: Specify ranges of public IP addresses using CIDR notation.

Access Control Within Autonomous AI Database on Dedicated Exadata Infrastructure

Contact Email

You can provide contact emails where you can receive operational notifications, announcements, and unplanned maintenance notifications regarding your Autonomous AI Database.

Oracle recommends using the email address of an administrator group rather than an individual's, whenever possible, to ensure no important notifications or announcements are missed.

Character Set

Autonomous AI Database lets you choose a character set of your choice from a list of supported character sets while provisioning an Autonomous AI Database.

You choose a Character Set and National Character Set while provisioning an Autonomous AI Database.

The list of supported character sets currently includes all database character sets supported on ASCII-based platforms.

Character Set Selection for Autonomous AI Database

Database In-Memory

You can enable Database In-memory for your Autonomous AI Database by allocating a percentage of its System Global Area (SGA) to the In-Memory column store (IM column store) either while provisioning the database or later. The In-Memory Column Store (IM column store) is the key feature of Database In-Memory. The IM column store maintains copies of tables, partitions, and individual columns in a special compressed columnar format optimized for rapid scans.

You can enable or disable Database In-Memory for an existing Autonomous AI Database from its Details page on the Oracle Cloud Infrastructure (OCI) console.

You can also enable Database In-Memory on databases cloned from a database instance or backup, irrespective of whether the clone source has Database In-memory enabled.

Database In-Memory

Database Cloning

You can clone an Autonomous AI Database, creating a point-in-time copy of it or its backup set. You can use the cloning feature to quickly set up an Autonomous AI Database with historical data for purposes such as testing, development, or analytics.

Autonomous AI Database supports the following clone types:

Full Clone: A full clone creates a new database that includes the metadata and data from the source database.
Metadata Clone: This clone type creates a new database that includes all source database schema metadata, but not the source database data.

About Cloning Autonomous AI Database on Dedicated Exadata Infrastructure

Ops Insights

Ops Insights is a cloud-native service that provides 360-degree insight into the resource utilization and capacity of databases and hosts. You can easily analyze CPU and storage resources, forecast capacity issues, and proactively identify SQL performance issues across your database fleet.

By default, Ops Insights is disabled for an Autonomous AI Database, and you must enable it from the Oracle Cloud Infrastructure console.

With Ops Insights, you can:

Analyze resource usage of databases/hosts across the enterprise.
Forecast future demand for resources based on historical trends.
Compare SQL Performance across databases and identify common patterns.
Identify SQL performance trends across enterprise-wide databases.
Analyze AWR statistics for database performance, diagnostics, and tuning across a fleet of databases.

Use Operations Insights on Autonomous AI Database on Dedicated Exadata Infrastructure

Get Started with Ops Insights

Autonomous AI Database Metrics

You can monitor the health, capacity, and performance of your Autonomous AI Databases with metrics, alarms, and notifications. The Autonomous AI Database metrics help you measure useful quantitative data, such as CPU and storage utilization, the number of successful and failed database logon and connection attempts, database operations, SQL queries, and transactions, and so on. You can use metrics data to diagnose and troubleshoot problems with your Autonomous AI Database resources.

You can use Oracle Cloud Infrastructure console or Monitoring APIs to view metrics.

Monitor Databases with Autonomous AI Database Metrics

Data Safe

Oracle Data Safe helps you understand the sensitivity of your data, evaluate risks to data, mask sensitive data, implement and monitor security controls, assess user security, monitor user activity, and address data security compliance requirements in your databases.

Oracle Data Safe provides the following set of features in a single, easy-to-use management console:

Security Assessment helps you assess the security of your database configuration.
User Assessment helps you assess the security of your database users and identify high risk users.
Data Discovery helps you find sensitive data in your database. Data Masking provides a way for you to mask sensitive data so that the data is safe for non-production purposes.
Activity Auditing lets you audit user activity on your database so you can monitor database usage and be alerted of unusual database activities.

Before you can register your database with Data Safe, Data Safe must be configured to access databases in your dedicated infrastructure configuration.

Oracle Data Safe Overview

Autonomous AI Database Tools

The following tools are available to Autonomous AI Database users:

Tool	Notes	Further Reference
Database Actions Oracle Database Actions is a browser-based application that provides development tools, data tools,administration, and monitoring features for Autonomous AI Database. Using Database Actions, you can load data and run SQL statements, queries, and scripts in a worksheet, export data, create Data Modeler diagrams, and enable database administrators to monitor the database.	You can connect to Autonomous AI Database using Database Actions without downloading or installing additional software on your system. Oracle Database Actions runs in Oracle REST Data Services and access to it is provided through schema-based authentication. To use Oracle Database Actions, you must sign in as a database user whose schema has been enabled for Database Actions.	About Oracle Database Actions Connect to Autonomous AI Database with Database Actions
Oracle APEX (Oracle Application Express) Oracle APEX provides you with an easy-to-use browser-based environment to load data, manage database objects, develop REST interfaces, and build applications.	Configuration, patching, monitoring, and upgrading all Oracle Application Express components are fully managed by Oracle. There are no limits on the number of developers or end-users for your Oracle APEX applications. Autonomous AI Database can instantly scale compute and storage online as needed, based upon your workload. You can deploy the Oracle APEX applications developed on-premise to Oracle APEX on Autonomous AI Database, or vice-versa easily.	Build an APEX Application
SQLPlus SQLPlus is a command-line interface used to enter SQL commands. You can connect to Autonomous AI Database using SQL*Plus to define the database's tables, views, triggers, types, sequences and so on.	To be able to connect SQLPlus to an Autonomous AI Database, the system running SQLPlus must have network access to the Autonomous AI Database.	Connect with SQL*Plus
SQLcl (Oracle SQL Developer Command Line) SQLcl is a command-line interface for Oracle Database. It allows you to interactively or batch execute SQL and PL/SQL. SQLcl provides in-line editing, statement completion, and command recall for a feature-rich experience, all while also supporting your previously written SQL*Plus scripts.	To be able to connect SQLCl to an Autonomous AI Database, the system running SQLCl must have network access to the Autonomous AI Database.	Connect wth Oracle SQLcl
SQL Developer Oracle SQL Developer is a free integrated development environment that simplifies the development and management of Oracle Database in both traditional and cloud deployments. SQL Developer offers complete end-to-end development of your PL/SQL applications, a worksheet for running queries and scripts, a DBA console for managing the database, a reports interface, a complete data modeling solution, and a migration platform for moving your 3rd party databases to Oracle.	To be able to connect SQL Developer to an Autonomous AI Database, the system running SQL Developer must have network access to the Autonomous AI Database.	Connect with Oracle SQL Developer
Oracle REST Data Dervices Oracle REST Data Services (ORDS) makes it easy to develop REST interfaces for relational data in an Autonomous AI Database. ORDS is a mid-tier Java application that maps HTTP(S) verbs, such as GET, POST, PUT, DELETE, and so on, to database transactions, and returns any results as JSON data.	The Oracle REST Data Services (ORDS) application in Autonomous AI Database is preconfigured and fully managed. ORDS connects to the database using the `low` predefined database service with a fixed maximum number of connections (the number of connections for ORDS does not change based on the number of CPUs). It is not possible to change the default ORDS configuration.	Developing RESTful Services in Autonomous AI Database
Simple Oracle Document Access (SODA) Oracle provides a family of Simple Oracle Document Access (SODA) APIs for access to JSON data stored in the database. SODA is designed for schemaless application development without knowledge of relational database features or languages such as SQL and PL/SQL. It lets you create and store collections of documents in Oracle Database, retrieve them, and query them, without needing to know how the documents are stored in the database.	You can download the SODA drivers from the Details page of an Autonomous AI Database. There are available implementations of SODA are: SODA for REST SODA for Java: SODA for PL/SQL SODA for C SODA for Node.js SODA for Python	Overview of SODA
Oracle Database API for MongoDB Oracle Database API for MongoDB translates the MongoDB wire protocol into SQL statements that are executed by Oracle Database. It lets developers who have MongoDB skill sets write JSON document-store applications for Oracle Database that use drivers and tools that understand the MongoDB protocol.	To use the MongoDB API with an Autonomous AI Database, you must install and configure customer managed Oracle REST Data Services (ORDS) separately, and the version of ORDS must be 22.3 or later.	Overview of Oracle Database API for MongoDB

Autonomous AI Database Management Operations

You can perform the following management operations on an Autonomous AI Database.

The above listed operations can also be achieved using API. See API to Manage Autonomous AI Databases for further reference.

Title and Copyright Information

Oracle and/or its affiliates.

Operation	Task Instructions
Create an Autonomous AI Database	Create an Autonomous AI Database
Create an Elastic Pool	Create an Elastic Pool
Backup Your Autonomous AI Database Manually	Backup an Autonomous AI Database Manually
Clone an Autonomous AI Database	Clone an Autonomous AI Database
Create a Long-Term Backup	Create a Long-Term Backup
Enable or Disable Auto Scaling of an Autonomous AI Database	Enable or Disable Auto Scaling of an Autonomous AI Database
Enable or Disable Database In-Memory	Enable or Disable Database In-Memory
Enable Ops Insights for an Autonomous AI Database	Enable Ops Insights for an Autonomous AI Database
Join or Leave an Elastic Pool	Join or Leave an Elastic Pool
Manage an Elastic Pool as a Pool Leader	Manage an Elastic Pool as a Pool Leader
View Details of an Autonomous AI Database	View Details of an Autonomous AI Database
Manage Customer Contacts for an Autonomous AI Database	Manage Customer Contacts for an Autonomous AI Database
Manage CPU or Storage Resources of an Autonomous AI Database	Manage CPU or Storage Resources of an Autonomous AI Database
Manage Long-Term Backups	Manage Long-Term Backups
Manage Primary and Standby Databases in Autonomous Data Guard Configuration	Manage Primary and Standby Databases in an Autonomous Data Guard Configuration
Move an Autonomous AI Database to a Different Compartment	Move an Autonomous AI Database to a Different Compartment
Restore and Recover Your Autonomous AI Database	Restore and Recover Autonomous AI Database
Start, Stop, and Restart an Autonomous AI Database	Start, Stop, and Restart an Autonomous AI Database
View Autonomous AI Database Metrics for a Database	View Autonomous AI Database Metrics for a Database
View Autonomous AI Database Metrics for Databases in a Compartment	View Autonomous AI Database Metrics for Databases in a Compartment
Download Client Credentials	Download Client Credentials
View Connection Strings for an Autonomous AI Database	View Connection Strings for anAutonomous AI Database
Set Access Control List for an Autonomous AI Database	Set Access Control List for an Autonomous AI Database
Register or Deregister a Dedicated Database with Data Safe	Register or Deregister a Dedicated Database with Data Safe
Terminate an Autonomous AI Database	Terminate an Autonomous AI Database
Undelete an Autonomous AI Database	Undelete an Autonomous AI Database