What’s New for Oracle Autonomous AI Database Serverless

Here’s a summary of the noteworthy Oracle Autonomous AI Database additions and enhancements.

See Previous Feature Announcements for 2025 announcements and older announcements.

• May 2026
  
• April 2026
  
• March 2026
  
• February 2026
  
• January 2026
  

May 2026

Feature	Description
Automatic management of roles and privileges during migration	Autonomous AI Database automatically converts or suppresses unsupported grant and revoke operations, maps roles to their supported equivalents, and maintains a transparent audit trail in the DBA_CONVERTED_STATEMENTS view. See Manage Roles and Privileges when Migrating to Autonomous AI Database for more information.
Zero Data Loss Protection with Local Autonomous Data Guard Standby	For Autonomous Data Guard, zero data loss protection (RPO = 0) is provided for a local standby database. Autonomous Data Guard performs automatic failover to a local standby database when a standby is available and the system guarantees zero data loss. If a data loss limit is specified (0 to 3600 seconds), failover occurs within the defined limit. See Use Standby Databases with Autonomous Data Guard for Disaster Recovery for more information.
Absolute Path Support in CREATE DIRECTORY	Autonomous AI Database accepts absolute paths in CREATE DIRECTORY statements and creates directories under managed locations for migration compatibility. See Create Directory in Autonomous AI Database for more information.
Migrate Data with DBMS_CLOUD_IMPORT	You can use DBMS_CLOUD_IMPORT to import data into Autonomous AI Database. DBMS_CLOUD_IMPORT supports Oracle source databases as well as non-Oracle databases, for example, MySQL, PostgreSQL, and Amazon Redshift. You can import either the entire or the subset of the data stored in a supported source database. See Migrate Data with DBMS_CLOUD_IMPORT for more information.
Reduced Steps for Network Configuration Switching	Autonomous AI Database allows seamless switching from Private endpoint access to Secure access from allowed IPs and VCNs only without any TLS changes, preserving your existing configuration. See Change from Private to Public Endpoints with Autonomous AI Database for more information.
Improved Outbound Connection options for Private Endpoints on Oracle Autonomous AI Database 26ai	When you define a private endpoint for your Autonomous AI Database 26ai instance, you can provide enhanced security by setting a database property to enforce that all outgoing connections to a target host are subject to and limited by the private endpoint's egress rules. For more details, see Enhanced Security for Outbound Connections with Private Endpoints.
Multifactor Authentication in Autonomous AI Database 26ai	Autonomous AI Database 26ai supports Multifactor Authentication (MFA) to strengthen database access security by requiring an additional verification factor in addition to the user password. MFA can be configured for database login, for running protected SQL statements, or for both. For more details, see Use Multifactor Authentication with Autonomous AI Database.
Data Transforms Enhancements	Data Transforms includes the following new features and changes: OCI Vault Integration for Connections Data Transforms integrates with OCI Vault to allow the use of vault secret credentials to authenticate connections. See Use OCI Vault Secret Credentials for Connections. Image Vector Embeddings in Data Flows You can add image vector embeddings in a data flow using the Oracle Cloud Infrastructure (OCI) Generative AI service. In the Data Flow Editor, use the Image Embedding Vector operator within the Machine Learning database function to convert input images to vector embeddings. For more information, see Use Embedding Vectors in a Data Flow. Capture Auditing Information for Data Loads The Settings button on the Data Load Detail page now includes options that you can use to add auditing data columns when you run a data load. See Run a Data Load for more details. Collect and Publish Statistics for Iceberg tables The Workflow editor includes the Iceberg Stats step that lets you collect and publish statistics for Iceberg tables and publish them to external tables. You can use the step independently or add an Iceberg data load to the work flow, and then add Iceberg Stats as a step to collect table and column statistics and publish them to an external table. See Collect and Publish Iceberg Table Statistics to External Tables in Create an Apache Iceberg Connection. Enhancements to the Job Details page The steps that are displayed on the Job Details page are now categorized in different nodes for ease of reference. These include Admin Jobs, Execution Sets, and Tables. See Create and Manage Jobs for more information about the Job Details page. Load Data to Apache Iceberg tables using Snowflake Open Catalog You can use Snowflake Data Catalog when you create an Apache Iceberg connection to load data. You can use AWS S3 storage services for storing data into Apache Iceberg as target tables. See Create an Apache Iceberg Connection for detailed instructions. Support for Apache Iceberg Parquet File Clustering and Compaction Data Transforms supports the Iceberg clustering and compaction features to mitigate increased storage costs and optimize query performance. You can add an Iceberg data load to the work flow, and then add Iceberg Clustering and Compaction as a step. You can then schedule the workflow to run the data load and then execute clustering and compaction on the loaded data. See Parquet File Clustering and Compaction in Create an Apache Iceberg Connection. Load Data into Oracle Fusion Incentive Compensation tables Oracle Data Transforms enables ingestion of Oracle Fusion Incentive Compensation data from CSV files stored in Oracle Object Storage into Oracle Fusion Incentive Compensation tables. See Create and use an Oracle Fusion Incentive Compensation Connection. Load Data into Oracle Fusion Subscription Management tables You can use Oracle Data Transforms to stage and load subscription-related data from CSV files stored in Object Storage into the Oracle Fusion Subscription Management application tables. See Create and use an Oracle Fusion Subscription Management Connection. Additional Connection Types Data Transforms includes support for the MariaDB and Sage Intacct application connection types in this release. For the complete list of supported connection types, see Supported Connection Types.

April 2026

Feature	Description
Extend Select AI translate support to Google, AWS, and Azure	The Translate feature enables you to translate text across multiple languages using SQL or PL/SQL, based on the AI provider configured in your AI profile. This feature supports multiple providers, including OCI, Google, AWS, and Azure. See Translate, Example: Select AI Translate, TRANSLATE Function, and GENERATE Function to explore this feature.
Oracle Spatial Studio	Oracle Spatial Studio provides a no-code user interface to access the spatial features of Oracle Database. The interface supports spatial data loading, preparation, visualization, and analysis. Spatial Studio is a fully integrated feature of Autonomous AI Database and appears in the Tool Configuration Tab on the Autonomous AI Database Details page. It is available only for the Elastic CPU (ECPU) model. See Use Oracle Spatial with Autonomous AI Database for more information.
Secret-Based Password Authentication for Autonomous AI Database Users	With secret- based password authentication, you can create and manage database users whose passwords are stored as secrets in a cloud provider’s vault and referenced through a vault secret credential. The database fetches the password from the vault during authentication, generates verifiers only in memory, and does not persist passwords or verifiers on disk. See Create Users with Secret-Based Password Authentication and Update User Password with Secret-Based Password Authentication for more information.
Granular Permissions for Autonomous AI Database Policies	The actiontype variables in Autonomous AI Database enables precise control over sub-operations like adminPassword, scheduledOperations, manageEncryptionKeys, and more during database creation or updates. This supports separation of duties, least-privilege access, and compliance, without disrupting existing broad permissions. See Policy Details for Autonomous AI Database for more information.

March 2026

Feature	Description
Select AI for Property Graphs	Select AI supports natural language to SQL (NL2SQL) generation for SQL Property Graphs. You can include one or more property graphs in an AI profile object list and issue natural language prompts that Select AI converts into PGQ (Property Graph Query) statements using the GRAPH_TABLE operator. This feature enables users to query and analyze graph-structured data without manually writing complex PGQ syntax. See Select AI for Property Graphs, Example: Select AI for Property Graphs, and Example: Sample Prompts for Property Graphs for more details.
Send Database Identity Network Headers for Outbound HTTP Request	Database Identity Network Headers in Autonomous AI Database adds database identity metadata as a JSON X-header to outbound UTL_HTTP calls so remote endpoints can verify which Autonomous AI Database (and tenant) is calling them. See Send Database Identity Network Headers for Outbound HTTP Requests for more information.
Monitor Autonomous AI Database Memory Utilization	Two new memory utilization metrics for monitoring SGA and PGA Utilization are now available an Autonomous AI Database. See Available Metrics: oci_autonomous_database for more information.
Clone ADMIN Privileges in Autonomous AI Database	You can use the DBMS_CLOUD_ADMIN_SEC package to clone the privileges and permissions assigned to the ADMIN user for a specified user account in Autonomous AI Database. This enables administrators to create named user accounts with the same privileges as the ADMIN user. It provides an alternative to using the shared ADMIN account improving security. See DBMS_CLOUD_ADMIN_SEC Package for more information.
Single Sign-On Support for all Autonomous AI Database Tools	You can access built-in tools in your Autonomous AI Database with single sign-on. You must log in once with your database credentials to switch between tools such as Oracle APEX, Database Actions, Graph Studio, Oracle Machine Learning, and Oracle Data Transforms without re-authenticating. See Access Built-in Tools with Single Sign-on for more information.

February 2026

Feature	Description
Multifactor Authentication in Autonomous AI Database	Autonomous AI Database supports Multifactor Authentication (MFA) to strengthen database access security by requiring an additional verification factor in addition to the user password. MFA can be configured for database login, for running protected SQL statements, or for both. For more details, see Use Multifactor Authentication with Autonomous AI Database.
Dataplane Event: ConnectionDropsDetected	The ConnectionDropsDetected event is generated when a significant number of connection drops are observed for your Autonomous AI Database. For more details, see Information Events on Autonomous AI Database.
Data Transforms Enhancements	Data Transforms includes the following new features and changes: Configure Timezone to Run Schedules You can set the default timezone for running schedules using the new Settings page under the Administration tab. The configuration you set here appears as the default selection on the Create Schedule page. Note that you can choose a different timezone when you create a schedule. See Set Timezone to Run Schedules. Set Desired Border Color to your Data Transforms Instance You can apply distinct colors to your Data Transforms environments to differentiate between them. The Settings page under the Administration tab includes a color palette that you can choose from to set the color. The selected color appears as a border around the user interface. See Apply Color Coding to Oracle Data Transforms Environments. Provisioning UI Enhancements When you log in to your Autonomous Database environment, you now see a splash screen that displays a slide show of the capabilities of Data Transforms. Advanced options for Apache Iceberg You can now set the Batch Update Size for Apache Iceberg connections to control the number of records that are updated on the target table at a time. This helps improve performance of data load runs. See Create an Apache Iceberg Connection.

January 2026

Feature	Description
Select AI Proxy Integration	Use an Autonomous AI Database as a Select AI Proxy to securely integrate with Oracle and non-Oracle databases and bring natural language queries to these databases by routing requests through Autonomous AI Database. For more details, see Use an AI Data Gateway for Select AI NL2SQL.
Monitoring Metrics for OCI Autonomous AI Database	Resource utilization metrics are available for monitoring Autonomous AI Databases. For more details, see Available Metrics: oci_autonomous_database.
Incremental refresh of materialized views over Cloud Links	With incremental refresh of materialized views over Cloud Links, the Autonomous AI Database refreshes only changed data from remote tables instead of recomputing the entire materialized view. The MV_FAST_REFRESH parameter in the REGISTER and UPDATE_REGISTRATION procedures of the DBMS_CLOUD_LINK package enables providers to explicitly support fast refresh for cloud links. This fast refresh capability improves dashboard and report performance and provides real-time analytics. For more details, see Optimize Cloud Links Performance with Materialized Views.
Online restart option for Autonomous AI Database	Oracle Autonomous AI Database provides two restart options: a standard Restart, and an Online restart that reduces downtime. With Online restart, the Autonomous AI Database instance is restarted with minimal impact on database availability. For more details, see Restart Autonomous AI Database
Improved Outbound Connection options for Private Endpoints	When you define a private endpoint for your Autonomous AI Database instance you can provide enhanced security by setting a database property to enforce that all outgoing connections to a target host are subject to and limited by the private endpoint's egress rules. For more details, see Enhanced Security for Outbound Connections with Private Endpoints.
Support cloud link sharing with MY$POOL scope in Elastic Pool.	With MY$POOL scope in cloud links, you can register datasets once in a provider Autonomous AI Database, making them discoverable and queryable from any other Autonomous AI Database in the same Elastic Pool. Scope checks are enforced on the consumer side to ensure proper access control. See Grant Cloud Links Access for Database Users for more information.