Oracle AI Database 26ai Powers the AI for Data Revolution

A big update to Oracle’s most popular database builds AI into its core, making it work with all types of data and workloads without any problems.

Allows customers to get new ideas, insights, and work done across both multicloud and on-premises settings

The Apache Iceberg open table format can now be used with the new Oracle Autonomous AI Lakehouse. This lets customers use the power of Oracle AI Database for their data lake data.

The 26th Oracle AI Database ai builds AI into the core of data management. This is another way that Oracle is helping companies safely add AI to all of their data, everywhere. This achievement moves Oracle’s “AI for Data” idea of a next-generation AI-native database forward. This database will use AI in all areas of data and development, such as AI Vector Search, AI for Database Management, AI for Data Development, AI for Application Development, and AI for Analytics. Customers can now use dynamic agentic AI processes to get smart answers and take actions that use both private and public database data.

Juan Loaiza, executive vice president of Oracle Database Technologies, said, “By building AI and data together, Oracle AI Database makes ‘AI for Data’ easy to learn and use.” “We make it easy for our customers to get trusted AI insights, new ideas, and increased productivity for all of their data, in all of their systems, including operational data lakes and analytic data lakes.”

Oracle’s “AI for Data” approach is widely known and open to everyone. Customers of Oracle AI Database have a lot of options when it comes to building and deploying AI applications. These options include support for the Apache Iceberg open table format, Model Context Protocol (MCP), industry-leading LLMs, popular agentic AI frameworks, and Open Neural Network Exchange (ONNX) embedding models. Oracle AI Database’s mission-critical features add AI to data in a safe, efficient, and reliable way, no matter where it lives: in Oracle Cloud, a private cloud, a top hyperscale cloud, or on-premises.

Oracle AI Database uses ML-KEM, a quantum-resistant algorithm approved by NIST, to secure data as it travels. With the built-in support for quantum-resistant encryption for data-at-rest, Oracle AI Database’s data security method is meant to stop hackers from stealing company data now and later decrypting it with quantum computers. Other companies have only put quantum-resistant algorithms in one of their network and storage architectures or database services. They haven’t done both.

“Good AI needs good data.” People can get both with Oracle AI Database 26ai. It is the only place where their up-to-date, consistent, and safe business info is kept. VP and senior analyst at Constellation Research Holger Mueller said, “That’s where you should put that data if you want to use AI on it without having to move it.” “AI Database 26ai has great new AI features that go beyond AI Vector Search to make using AI easier and faster.” One great thing about Oracle is that they built Agentic AI into the database, which lets users create, deploy, and manage their own AI agents inside the database using a visual platform that doesn’t require any code and comes with ready-made agents. Oracle is the clear leader in converged databases for transaction processing, and its place as the leader in data and AI keeps growing quickly.

The long-term support release Oracle AI Database 26ai takes the place of Oracle Database 23ai. Customers can easily switch from 23ai to the features of 26ai that are already available by applying the October 2025 release update. Customers will get the features that are available right away and will be ready for new features as they come out. There is no need to upgrade the database or re-certify the program. There is no extra charge for the advanced AI functions like AI Vector Search.

Key Points for Oracle AI Database 26ai

1. AI and analytics for the whole company
2. Autonomous AI Lakehouse: For AI and analytics at the business level, it supports the Apache Iceberg open table format.
3. It works with Databricks and Snowflake and is available on OCI, AWS, Azure, and Google Cloud.
4. It has Exadata speed, serverless pay-per-use scaling, and it works with other data tools.
5. 2. Basic technologies for AI
6. AI Vector Search is combined with relational, text, JSON, location, and graph searches to make it easier to find more data.
7. MCP Server Support—Allows AI agents to search through company records and improve outcomes by using repeated reasoning.
8. Built-in Data Privacy Protection: Row-, column-, and cell-level limits and dynamic masking make sure that data is kept safe.
9. Oracle Exadata for AI speeds up vector queries, makes the system more flexible with Exascale design, and lets you use it on multiple clouds (OCI, Azure, and Google Cloud).
10. Private AI Services Container: This container runs private AI models (LLMs, embeddings, and NERs) in safe, customer-controlled settings, such as in the cloud, privately, or on-premises.
11. AI acceleration with NVIDIA—works with NVIDIA NeMo Retriever and will allow GPU acceleration in the future through CAGRA (cuVS) for faster vector processing.

3. Using AI to Improve App Development

Data Annotations: Add information about the data that helps AI understand and use it better.

It combines relational, JSON, and graph models to make accessing data easier and more customisable.

Select AI Agent—Allows you to make and handle in-database AI agents that can securely automate workflows with multiple steps.

AI Private Agent Factory provides a no-code AI agent maker that can be used anywhere and protects data privacy while allowing for growth.

APEX AI Application Generator: This tool helps developers make business apps more quickly by using natural language.

4. Innovations that are mission-critical

Protect your databases in real time and get them back after ransomware attacks with OCI Zero Data Loss Cloud Protect.

Globally Distributed Database: Protects the ownership of data, allows for massive expansion, and provides active-active replication with backup in less than three seconds.

With full support for SQL, JSON, Spatial, and Graph, True Cache automatically keeps transactional stability across mid-tier caches.

SQL Firewall: Protects against unauthorised SQL searches and injection attacks right out of the box.

To sum up

Oracle AI Database 26ai combines self-driving speed, AI for large businesses, and design that puts security first.

Businesses can use it to run AI-driven analytics, keep secret AI workloads safe, and make smart apps, all while making sure they are compliant, scalable, and don’t lose any data.