Run AI on all your data in a simple, secure, and pay-per-use manner, using the best of open source data lake technologies and enterprise data warehouse capabilities for elastic multicloud data management.
It combines Oracle Autonomous AI Database with vendor-independent Apache Iceberg, enabling customers to run AI and analytics securely on all their data—available on OCI, AWS, Azure, Google Cloud, and Exadata Cloud@Customer.
Any cloud, any data, any location, and any workload. Unleash the full potential of your all data with an open and standards-based cloud lakehouse platform designed for today’s most demanding analytics needs.
Integrate seamlessly with any data lake and share data using leading open-source protocols, enabling collaboration and flexibility across hybrid and multicloud environments.
With end-to-end, always-on security and robust governance, giving you peace of mind without extra costs or complexity.
Accelerate innovation with built-in AI, vector search, and machine learning, including intuitive features, such as Select AI, enabling everyone to easily harness the power of analytics—no SQL or coding expertise required.
Scale effortlessly and deploy anywhere—Oracle Cloud, AWS, Azure, Google Cloud, or on-premises—achieving high performance and easy access to data wherever it resides.
Unify all your analytic workloads on a single platform, connecting to open table formats and more than hundreds of database and application sources along with native support for structured, semi-structured, and unstructured data types.
Experience fully managed, autonomous operations that eliminate administrative overhead and simplify analytics. So you can focus on insights, not infrastructure.
Read the IDC Business Value report on Oracle Autonomous AI Database.
Autonomous AI Lakehouse integrates with open data platforms across any cloud via Apache Iceberg, letting you query Iceberg tables in place with Oracle AI Database 26ai’s built-in AI, machine learning, graph, and spatial—without data movement. Discover and access Iceberg data across clouds through a unified Catalog in Autonomous AI Lakehouse, then accelerate performance with Data Lake Accelerator for petabyte-scale scans and table caching for fast repeat queries.
Operate in true multicloud by blending lakehouse data with your enterprise data via simple SQL and complement workflows with high performance Spark and Python integration.
Autonomous management capabilities, such as provisioning, configuring, securing, tuning, and scaling, eliminate nearly all the manual and complex tasks that can introduce human error. Autonomous management enables customers to run a high performance, highly available, and secure data warehouse and lakehouse while running thousands of databases with no administration.
Autonomous AI Lakehouse Data Catalog provides detailed information about entities within and available to the database, including data sets, their sources, how they were created, and the impact of changes to source data on dependent objects. This includes database objects, such as business models, cloud storage links, tables (including Apache Iceberg tables), columns, and analytic views. The catalog supports integration with external data sources, enabling data search, discovery, and use across a wide range of systems, including other Autonomous AI Databases, on-premises databases, cloud storage systems, shared data, and external data catalogs, like Oracle Cloud Infrastructure Data Catalog and AWS Glue, as well as Apache Iceberg catalogs, such as those in Databricks and Snowflake. This multi-catalog capability allows users to seamlessly link and manage data from diverse environments.
The Data Studio Data Sharing feature allows users to provide and consume data shares directly from the Data Studio Overview page. The platform supports bidirectional data sharing, enabling secure and efficient data exchange across multiple clouds and platforms, including with external partners and other cloud services, such as Power BI and Tableau. This capability is enhanced by the implementation of the open source Delta Sharing protocol, which allows for real-time, secure data sharing without data duplication or code modification.
The Data Marketplace is a platform that enables users to access, discover, and share datasets seamlessly with Autonomous AI Database. It is part of the Data Studio toolset, designed for data scientists and business users to load, query, and analyze datasets based on organizational needs. Users can integrate shared data with existing data and augment it using AI capabilities such as language detection, sentiment analysis, and key phrase extraction.
Secure Autonomous AI Lakehouse with a unified database security control center that identifies sensitive data and masks it, issues alerts on risky users and configurations, audits critical database activities, and discovers suspicious attempts to access data.
Data Studio is built into Autonomous AI Lakehouse, offering users simple and intuitive self-service data engineering tools for loading, transforming, analyzing, and sharing data with internal and external stakeholders. Its built-in catalog enables users to discover data assets in databases, object stores, and data lakes.
Business and data analysts can easily integrate data from more than 100 application, cloud service, and database sources with drag-and-drop workflow capabilities. Oracle Autonomous AI Database Data Studio also lets users generate business models, quickly discover anomalies and hidden patterns, understand critical data dependencies, and access all organizational data located in databases and data stores.
Ask questions in natural language and instantly access your data where it lives. Autonomous AI Lakehouse Select AI turns plain‑English prompts into SQL to query all your data directly across databases, files, and lakehouse tables—no complex integration or data movement. Bring AI to the data with your choice of leading large language models (LLMs) and embedding models (Cohere, Azure OpenAI, OpenAI, OCI Generative AI, Google, Anthropic, Hugging Face, AWS, and more) under enterprise security, policies, and access controls.
Build and deploy machine learning where the data already resides. Oracle Machine Learning runs scalable, in-database algorithms so models train and score next to your data, preserving governance, minimizing latency, and accelerating time to value.
Autonomous AI Lakehouse includes graph database features to represent and manage complex data relationships in simple SQL, without data movement. The graph analytics enable data scientists and developers to apply pattern recognition, classification, and statistical analysis for deeper context. Run enterprise-grade graph analytics at scale directly on your lakehouse data in your Autonomous AI Lakehouse with data in object store, like Apache Iceberg tables.
The spatial features in Autonomous AI Lakehouse address all forms of applications, spatial workloads, and data sets, including the most demanding, large-scale location intelligence and geospatial applications.
Use Oracle Spatial Studio, a self-service application, to create interactive maps and perform spatial analysis on business data quickly and easily. Visualize, explore, and analyze geospatial data stored in and managed by Autonomous AI Lakehouse.
Easily bring AI-powered similarity search to your business data without managing and integrating multiple databases or compromising functionality, security, and consistency.
AI Vector Search enables enterprises to store, index, and retrieve unstructured data using AI-powered semantic understanding, allowing for contextual search on your data—such as customer reviews, technical knowledgebase, sales calls and CRM notes, and multimedia content. It also enables ultra-sophisticated AI search applications.
Native AI vector search capabilities can also help LLMs deliver more accurate and contextually relevant results for enterprise use cases using retrieval-augmented generation (RAG) on your business data.
Industry data models are focused on Oracle application accelerators for Oracle’s E-Business Suite, Fusion Applications, and NetSuite provide enhanced analytical capabilities with self-service data discovery, built-in ETL, and KPI metrics. Users can do more with comprehensive data integration and ready-to-use data models.
Our application accelerators offer prebuilt ETL, enabling users to quickly create data warehouses from Oracle E-Business Suite data.
Oracle Fusion Analytics Warehouse and Oracle NetSuite Analytics Warehouse are built on Autonomous AI Lakehouse, and they both provide an end-to-end cloud data warehouse and analytical solution.
For custom-built data warehouses, Autonomous AI Lakehouse provides comprehensive data transformation flows that connect to Oracle and third-party applications.
Accelerate innovation by putting the power and flexibility of Autonomous AI Lakehouse in all of the leading hyperscalers. Combine the best of your preferred cloud with Autonomous AI Lakehouse to quickly build and modernize enterprise-scale applications.
Leverage each hyperscaler's native cloud services for AI, security, and data integration along with their preferred choice of business intelligence tools for immediate insights. Take advantage of simplified monitoring and troubleshooting with service logs, metrics, and events available directly in OCI, AWS, Azure, and Google Cloud.
Purchase Oracle AI Database services through AWS, Azure, and Google Cloud Marketplace with your current cloud commitments and/or use current Oracle AI Database licenses and unlimited license agreements.
The latest release of Oracle’s flagship database architects AI into its core, seamlessly integrating AI across all major data types and workloads.
Accelerate innovation and cloud migration with the power and flexibility to deploy OCI Oracle AI Database services in any cloud. Combine the best of the cloud with your data to quickly build and modernize applications.
Advance your AI and multicloud strategies with Oracle’s latest innovations in database and cloud technologies. Watch the on-demand sessions to learn more.
Gartner recognizes Oracle as a Leader in the Magic Quadrant for Strategic Cloud Platform Services.
Top-rated software and services based on in-depth reviews from verified users.
Average annual benefits per organization
Three-year return on investment
Availability with zero-downtime upgrades2
More productive analytics teams
Less time for analytics teams to run queries
Introducing Autonomous AI Lakehouse, enabling an open and interoperable lakehouse platform without compromise. It combines the trusted Autonomous AI Database with the openness of Apache Iceberg, eliminating analytic silos and accelerating AI development. Available across clouds, it delivers Exadata performance and security without vendor lock-in or data movement.
Read the complete postExplore Oracle Help Center for product documentation and other resources to deploy Autonomous AI Lakehouse.
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1. The Gartner Peer Insights logo is a trademark and service mark of Gartner Inc. and/or its affiliates and is used herein with permission. All rights reserved. Gartner Peer Insights reviews constitute the subjective opinions of individual end-user reviews, ratings, and data applied against a documented methodology; they neither represent the views of, nor constitute an endorsement by, Gartner or its affiliates.
2. The service level agreement (SLA) for 99.995% availability assumes the use of Oracle Autonomous Data Guard. The SLA is 99.95% availability when Autonomous Data Guard isn’t enabled.
Oracle Autonomous AI Lakehouse enables open, interoperable data access across multi-platform, multicloud environments
66% more efficient DBA teams. 48% more efficient IT infrastructure teams. 436% 3-year ROI.
Oracle AI Database 26ai powers the AI for data revolution
Multicloud solutions
Oracle DatabaseWorld: Multicloud AI Edition
Oracle named a Leader in Gartner® Magic Quadrant™

