Oracle AI Database 26ai Powers the AI for Data Revolution
Oracle (ORCL) on October 14, 2025 announced Oracle AI Database 26ai, a long‑term support release that architects AI into core data management to enable "AI for Data" across multicloud and on‑premises environments.
Key highlights include support for the Apache Iceberg open table format and an Oracle Autonomous AI Lakehouse available on OCI, AWS, Azure, and Google Cloud; built‑in AI Vector Search at no extra charge; MCP server support for agentic AI; NIST‑approved ML‑KEM quantum‑resistant encryption for data‑in‑flight; and Exadata Exascale performance and RDMA acceleration.
Oracle (ORCL) il 14 ottobre 2025 ha annunciato Oracle AI Database 26ai, una versione a lungo termine supportata che integra l'IA nel core della gestione dei dati per abilitare "IA per i dati" su ambienti multi-cloud e on‑premises.
I punti chiave includono il supporto al formato di tabella aperta Apache Iceberg e un Oracle Autonomous AI Lakehouse disponibile su OCI, AWS, Azure e Google Cloud; ricerca vettoriale AI integrata senza costi aggiuntivi; supporto MCP per l'AI agentico; cifratura resistente ai quantum ML-KEM approvata dal NIST per i dati in transito; e prestazioni Exadata Exascale e accelerazione RDMA.
Oracle (ORCL) el 14 de octubre de 2025 anunció Oracle AI Database 26ai, una versión de soporte a largo plazo que integra la IA en la gestión de datos central para permitir "IA para los datos" en entornos multicloud y locales.
Los aspectos destacados incluyen soporte para el formato de tabla abierto Apache Iceberg y un Oracle Autonomous AI Lakehouse disponible en OCI, AWS, Azure y Google Cloud; búsqueda vectorial de IA integrada sin costo adicional; soporte del servidor MCP para IA agencial; cifrado resistente a la cuántica ML-KEM aprobado por NIST para datos en tránsito; y rendimiento Exadata Exascale y aceleración RDMA.
Oracle (ORCL)는 2025년 10월 14일에 Oracle AI Database 26ai를 발표했습니다. 이는 다년간 지원되는 릴리스로 데이터 관리의 핵심에 AI를 설계하여 다중 클라우드 및 사내 환경에서 “데이터를 위한 AI”를 가능하게 합니다.
주요 하이라이트로는 Apache Iceberg 오픈 테이블 포맷 지원 및 OCI, AWS, Azure 및 Google Cloud에서 이용 가능한 Oracle Autonomous AI Lakehouse; 추가 비용 없이 제공되는 내장 AI 벡터 검색; 에이전틱 AI를 위한 MCP 서버 지원; 데이터 전송 중에 NIST 승인을 받은 ML-KEM 양자 저항 암호화; 그리고 Exadata Exascale 성능 및 RDMA 가속이 포함됩니다.
Oracle (ORCL) le 14 octobre 2025 a annoncé Oracle AI Database 26ai, une version à support à long terme qui intègre l'IA dans la gestion des données pour permettre "IA pour les données" sur des environnements multicloud et sur site.
Les points forts incluent le support du format de table ouvert Apache Iceberg et un Oracle Autonomous AI Lakehouse disponible sur OCI, AWS, Azure et Google Cloud; la recherche vectorielle IA intégrée sans coût supplémentaire; le support du serveur MCP pour l'IA agentique; le chiffrement ML-KEM résistant aux ordinateurs quantiques et approuvé par le NIST pour les données en transit; et les performances Exadata Exascale et l'accélération RDMA.
Oracle (ORCL) hat am 14. Oktober 2025 Oracle AI Database 26ai angekündigt, eine Langzeit-Support-Version, die AI in das Kerndatenmanagement integriert, um „AI for Data“ über Multi-Cloud- und On-Premises-Umgebungen zu ermöglichen.
Zu den wichtigsten Highlights gehören Unterstützung des Apache Iceberg Open-Table-Formats und ein Oracle Autonomous AI Lakehouse, verfügbar auf OCI, AWS, Azure und Google Cloud; integrierte AI Vektor-Suche ohne zusätzliche Kosten; MCP-Serverunterstützung für agentische KI; NIST-zugelassene ML-KEM-Quanten-resistente Verschlüsselung für Daten im Flug; und Exadata Exascale-Leistung sowie RDMA-Beschleunigung.
Oracle (ORCL) في 14 أكتوبر 2025 أعلن عن Oracle AI Database 26ai، إصدار دعم طويل الأجل يدمج الذكاء الاصطناعي في إدارة البيانات الأساسية لتمكين "الذكاء الاصطناعي من أجل البيانات" عبر بيئات متعددة السحابات وعلى التثبيت المحلي.
أبرز النقاط تشمل دعم تنسيق الجداول المفتوحة Apache Iceberg ووجود Oracle Autonomous AI Lakehouse المتاح على OCI وAWS وAzure وGoogle Cloud؛ بحث ناقل AI مدمج بدون تكلفة إضافية؛ دعم خادم MCP للذكاء الاصطناعي الوكيل؛ تشفير مقاوم للكم والضوء ML-KEM معتمَد من NIST للبيانات أثناء النقل؛ وأداء Exadata Exascale وتسريع RDMA.
Oracle (ORCL) 于 2025年10月14日 宣布 Oracle AI Database 26ai,这是一个长期支持版本,将 AI 纳入数据管理的核心,以在多云和本地环境中实现“数据的 AI”。
关键亮点包括支持 Apache Iceberg 开放表格式,以及在 OCI、AWS、Azure 和 Google Cloud 上可用的 Oracle Autonomous AI Lakehouse;内置的 AI 向量搜索,无需额外费用;用于代理式 AI 的 MCP 服务器支持;NIST 批准的 ML-KEM 量子抗性数据在传输中的加密;以及 Exadata Exascale 性能和 RDMA 加速。
- Supports Apache Iceberg and enterprise AI lakehouse on four clouds
- AI Vector Search included at no additional charge
- No database upgrade required from Database 23ai to 26ai
- Implements NIST‑approved ML‑KEM quantum‑resistant encryption for data‑in‑flight
- Exadata Exascale and RDMA accelerate AI vector queries and lower cost
- Several advanced AI features are listed as planned, not yet available
- Private AI Services Container currently runs on CPU only (GPU support planned)
- No pricing or commercial terms disclosed for new features
Insights
Oracle positions its flagship database as an AI-native platform across cloud and on-premises, simplifying in-database AI workflows.
Oracle AI Database 26ai integrates AI across search, development, analytics, and operations, and supports open standards such as Apache Iceberg and ONNX. The release replaces 23ai and promises no application recertification or database upgrade for customers who apply the
The business mechanism is consolidation: customers keep core data in one system while gaining vector search, agentic AI, and lakehouse access. Key dependencies include customer adoption of in-database agents, interoperability with hyperscalers, and uptake of the Autonomous AI Lakehouse on multiple clouds. Watch feature rollouts and enterprise uptake over the next 12–24 months, focusing on actual cross-cloud integrations and the availability of pre-built agents.
Built-in quantum-resistant encryption and in-database privacy controls aim to make AI on private data safer and compliant.
Oracle AI Database 26ai layers NIST-approved ML-KEM for data-in-flight and extends existing quantum-resistant protection for data-at-rest. It also provides row, column, and cell-level visibility rules, dynamic masking, and in-database enforcement to limit data exposure when LLMs access private data.
Risk depends on correct configuration and customer deployment choices for Private AI Services Container and Exadata acceleration. Monitor the actual default security settings, the deployment footprint of Private AI Services Containers, and proof points for ML-KEM in production within the next 6–18 months to validate the claimed protections.
Major release of Oracle's flagship database architects AI into its core, seamlessly integrating AI across all major data types and workloads
Enables customers to achieve breakthrough insights, innovations, and productivity across multicloud and on-premises environments
New Oracle Autonomous AI Lakehouse supports the Apache Iceberg open table format, enabling customers to use the power of Oracle AI Database for their data lake data
"By architecting AI and data together, Oracle AI Database makes 'AI for Data' simple to learn and simple to use," said Juan Loaiza, executive vice president, Oracle Database Technologies, Oracle. "We enable our customers to easily deliver trusted AI insights, innovations, and productivity for all their data, everywhere, including both operational systems and analytic data lakes."
Oracle's "AI for Data" strategy is open and ubiquitous. Oracle AI Database's built-in AI capabilities provide customers wide freedom of choice when building and deploying AI applications including 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 functionality brings AI to data securely, efficiently, and reliably wherever it resides—Oracle Cloud, leading hyperscale clouds, private cloud, or on-premises.
Oracle AI Database implements NIST-approved quantum-resistant algorithms (ML-KEM) to encrypt data-in-flight. Combined with the existing support for quantum-resistant encryption for data-at-rest, Oracle AI Database's data protection approach is designed to prevent hackers from harvesting organizational data now and decrypting it using quantum computers later. Other vendors have implemented quantum-resistant algorithms either in their network and storage architectures or in their database services, but not both.
"Great AI needs great data. With Oracle AI Database 26ai, customers get both. It's the single place where their business data lives—current, consistent, and secure. And it's the best place to use AI on that data without moving it," said Holger Mueller, vice president and principal analyst, Constellation Research. "To help simplify and accelerate AI adoption, AI Database 26ai includes impressive new AI features that go beyond AI Vector Search. A highlight is Oracle's architecting Agentic AI into the database, enabling customers to build, deploy, and manage their own in-database AI agents using a no-code visual platform that includes pre-built agents. As Oracle's converged database leadership in transaction processing goes unchallenged, its leadership position in the data and AI space continues to rise sharply as well."
Oracle AI Database 26ai is a long-term support release that replaces Oracle Database 23ai. Customers can simply apply the October 2025 release update to transition from 23ai to the currently available features of 26ai. Customers will receive the immediately available features and will be ready for additional features as they are released. There is no database upgrade or application re-certification required. Advanced AI features such as AI Vector Search are included at no additional charge.
Oracle AI Database 26ai features that are planned include:
Enterprise-wide AI and Analytics
- Oracle Autonomous AI Lakehouse: Supports the Apache Iceberg open table format, enabling true, enterprise-wide AI and analytics. It is now available on all four major hyperscalers—Oracle Cloud Infrastructure (OCI), Amazon Web Services, Microsoft Azure, and Google Cloud—and interoperable with Databricks and Snowflake on the same clouds. Autonomous AI Lakehouse enables customers to leverage their existing investments and gain the AI benefits of Autonomous AI Lakehouse for their business needs. Autonomous AI Lakehouse delivers Exadata-powered performance and pay-per-use serverless scaling. Learn more about Oracle Autonomous AI Lakehouse.
Foundational AI Technologies
- Unified Hybrid Vector Search: Combines AI Vector Search with relational, text, JSON, knowledge graph, and spatial searches—allowing retrieval of related documents, images, videos, audio, and structured data. Customers can easily combine AI Vector Search with LLMs to search for private data that an LLM can combine with public data to answer business questions.
- MCP Server Support: Enables AI Agents powered by LLMs to access an organization's database to answer questions using iterative reasoning. AI Agents can explore multiple solution paths and request additional data during their analysis to produce better and more accurate results.
- Built-in Data Privacy Protection: Enforces sophisticated security, privacy, and compliance rules in the database. Measures include end-user-specific row, column, and cell-level data visibility as well as dynamic masking of unauthorized data. In addition, it helps AI to access the database directly using SQL or other APIs without exposing private data.
- Oracle Exadata for AI: Accelerates AI at scale by delivering hardware and software engineered together for maximum performance and availability. Exadata can significantly accelerate AI vector queries by offloading them to Exadata intelligent storage. Vector offload also works with the new Exadata Exascale software architecture, which brings extreme elasticity and lower cost, extending Exadata benefits to smaller workloads and organizations. In addition, unique Remote Direct Memory Access (RDMA) algorithms further accelerate AI by enabling ultra low-latency and high-throughput data access from storage and across nodes in a cluster. Automatic data tiering delivers the low latency of memory, the high IOPS of flash, and the capacity of disk, while also reducing storage footprint using hybrid columnar compression (HCC). Finally, Exadata Database Service on Exascale Infrastructure supports Oracle Database 19c in OCI, Azure, and Google Cloud, enabling a much broader range of workloads to leverage Exadata's superior performance and scale.
- Private AI Services Container: Provides a prebuilt and tested environment for running private instances of AI models such as embedding models, open-weight LLMs, and Named Entity Recognizers. Use of this container helps enhance AI workload security since customers can avoid sharing data with third-party AI providers. The container can be deployed anywhere the customer chooses, within the customer's tenancy in the public cloud, on private clouds, or on-premises.
- AI Database Acceleration with NVIDIA: Oracle AI Database 26ai APIs that enable integration with LLM providers also support integration with NVIDIA NeMo Retriever microservices. Using this feature, Oracle AI Database 26ai can run vector embedding models or implement RAG pipelines using previously provisioned NVIDIA NIM microservices. In addition, Oracle Private AI Services Container, which currently supports execution on CPU resources, has also been designed to support the future use of NVIDIA accelerated computing for vector embedding and index generation using CAGRA (CUDA ANN GRAph-based algorithm) in the NVIDIA cuVS (GPU-Accelerated Vector Search) library.
AI for Application Development
- Data Annotations: Help explain the purpose, characteristics, and semantics of data to AI. This additional information helps AI generate better applications and provide more accurate responses to natural language questions.
- Unified Data Model: The relational, JSON, and graph data models have been unified, providing massive simplification. This accelerates developer productivity by enabling applications to access the same data in relational format via SQL, as a JSON document, or as a graph.
- Select AI Agent: Build, deploy, and manage AI agents within Oracle Autonomous AI Database with a simple, secure, and scalable in-database framework. It supports custom and pre-built in-database tools, external tools via REST, and MCP servers, enabling the automation of multi-step agentic workflows, accelerating innovation, and helping organizations keep their data safe.
- AI Private Agent Factory: Provides a no-code AI agent builder and deployment framework. These agents benefit from the full power, performance, scalability, and security of the converged data architecture of Oracle AI Database. It runs as a container in any environment of the customers' choosing to enhance data security—without customers having to share data with agentic frameworks on third-party clouds.
- APEX AI Application Generator: To boost developer productivity, Oracle plans to deliver next generation APEX development tools that use natural language interfaces to provide trusted answers to user questions and to generate enterprise-grade business applications.
Mission-critical Innovations
- Oracle Database Zero Data Loss Cloud Protect: Protects on-premises Oracle databases from data loss and ransomware using Oracle Zero Data Loss Recovery Service running in OCI. This includes real-time protection of database changes and enables fast recovery to any point-in-time.
- Globally Distributed Database: Supports ultra-scalability and data sovereignty by enabling a single logical database to be split into multiple parts and stored on different servers. Built-in RAFT-based replication enables multi-master, active-active distributed databases to fail over with zero data loss in less than three seconds.
- True Cache: Provides a unique application-transparent middle-tier cache that automatically ensures transactional consistency. Developers don't need to write code to populate and manage the data in the cache. True Cache brings the rich functionality of Oracle AI Database to mid-tier caches. All Oracle SQL, Vector, JSON, Spatial, and Graph query capabilities are also available via True Cache.
- SQL Firewall: Delivers in-database scalable protection against unauthorized SQL activity and injection attacks, enhancing security for all data in the database.
Additional Resources
- Watch Juan Loaiza's keynote at Oracle AI World
- Read the technical blog about Oracle AI Database 26ai
- Read what industry analysts are saying about Oracle AI Database 26ai
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The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle's products may change and remains at the sole discretion of Oracle Corporation.
Forward-Looking Statements Disclaimer
Statements in this article relating to Oracle's future plans, expectations, beliefs, and intentions are "forward-looking statements" and are subject to material risks and uncertainties. Many factors could affect Oracle's current expectations and actual results, and could cause actual results to differ materially. A discussion of such factors and other risks that affect Oracle's business is contained in Oracle's Securities and Exchange Commission (SEC) filings, including Oracle's most recent reports on Form 10-K and Form 10-Q under the heading "Risk Factors." These filings are available on the SEC's website or on Oracle's website at oracle.com/investor. All information in this article is current as of October 14, 2025 and Oracle undertakes no duty to update any statement in light of new information or future events
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