Oracle unveils Autonomous AI Lakehouse for seamless open data

Oracle has launched Oracle Autonomous AI Lakehouse, a data platform designed to provide open and interoperable data access across multi-platform, multicloud environments.

The new solution integrates Oracle Autonomous AI Database with the Apache Iceberg standard, enabling enterprises to process AI and analytics workloads securely on a broad range of data, regardless of storage location or vendor.

Oracle Autonomous AI Lakehouse is available on Oracle Cloud Infrastructure (OCI), Amazon Web Services (AWS), Microsoft Azure, Google Cloud, and Exadata Cloud@Customer environments.

Open access

According to Oracle, the adoption of the Apache Iceberg open standard is a significant step toward eliminating traditional data silos. Native support for Iceberg allows organisations to access, query, and manage data seamlessly across cloud providers and on-premises systems.

Çetin Özbütün, Executive Vice President, Autonomous Database Technologies at Oracle, explained the platform's approach.

"With Oracle Autonomous AI Lakehouse, we are offering customers a lakehouse platform without compromise by combining the highly trusted and industry-hardened Autonomous AI Database-executing in excess of 48 billion queries per hour-with the openness of Apache Iceberg," said Özbütün.

"Not only is Oracle breaking down the data silos between analytic systems with Iceberg, we are also enabling customers to access Iceberg data in any platform-operational or analytic-in the cloud or on-premises."

The platform integrates with data catalogs such as Databricks Unity, AWS Glue, and Snowflake Polaris, supporting seamless data operations and governance.

Users are able to run analytics and AI workloads on Iceberg tables and utilise functions including Select AI-which offers natural language-to-SQL capabilities-JSON-Relational Duality, Property Graph Analytics, and AI Vector Search. These features are underpinned by Exadata architecture, aiming to provide both performance and security while avoiding data movement between systems.

Partner and customer feedback

Interoperability was highlighted by partners involved in the launch. Stephen Orban, Senior Vice President, Product Ecosystem & Partnerships at Databricks, commented on the integrated approach.

"Customers consistently tell us they want to use the tools they already have on top of their data," said Orban. "Databricks is committed to open and interoperable data access for analytics and AI, and Unity Catalog helps make that possible by providing a unified governance layer for formats like Apache Iceberg. We welcome Oracle Autonomous AI Lakehouse's integration with Unity Catalog, giving joint customers seamless access to their data and the flexibility to use Oracle and Databricks together."

Oracle also introduced Data Lake Accelerator, which is designed to speed up large-scale queries on Iceberg tables by dynamically scaling network and compute resources as needed. This service operates under a consumption-based billing model.

Rosiane Porto of the Data Services Team - Big Data at SKY Brazil shared practical experience with the new feature:

"As part of Oracle's Limited Availability program for Data Lake Accelerator, SKY had the opportunity to test this new capability and was impressed by its performance," said Porto. "Data Lake Accelerator significantly improved query speeds on external data stored in object stores, enabling us to analyze large datasets faster and more efficiently-without moving data or changing our workflows. The ability to dynamically scale compute resources on demand gave us the flexibility to handle complex queries when needed, while keeping costs under control. We are excited about the potential of Data Lake Accelerator to simplify and accelerate external data processing for our business."

Key features

Oracle Autonomous AI Lakehouse includes several new components:

• Autonomous AI Database Catalog: Provides a unified view of enterprise data stored across cloud and on-premises assets, supporting connectivity to a variety of databases, lakes, data shares, and existing catalogs. The catalog is designed to improve collaborative data science, engineering, analysis, and AI processes.
• Autonomous AI Database Data Lake Accelerator: Automatically scales network and compute resources for queries against Iceberg tables based on demand.
• Select AI Agent: Offers an in-database framework enabling the deployment and management of AI agents, supporting PL/SQL tools, RESTful external tools, and MCP servers for automating workflows.
• Data Science Agent: Expected to enable users to leverage a pre-built AI assistant for tasks such as searching catalogs, data preparation, exploration, and insight generation using natural language interfaces.
• Plug and Play SQL Access: New SQL syntax intended to simplify querying of data across multiple catalog connections, with immediate query capability on Iceberg, AWS, Databricks, Snowflake, and Apache Gravitino.
• Exadata Table Cache: Improves query performance by storing frequently accessed Iceberg data within Oracle Exadata flash storage.
• GoldenGate for Iceberg: Supports real-time data streaming from operational and analytic sources to any Iceberg target, aiming for efficient integration of data from software-as-a-service (SaaS) applications and other sources.
• Table Hyperlink for Easy Data Sharing: Gives customers a secure method to share up-to-date data, internally or externally, by generating isolated temporary hyperlinks to tables or query results.

Ron Westfall, Vice President, Practise Lead, Networking and Infrastructure at HyperFRAME Research, commented on Oracle's embrace of Apache Iceberg and the move toward greater openness.

"The days of trade-offs between enterprise-grade scalability and open source flexibility are over," said Westfall.

"Oracle's support for Apache Iceberg with Autonomous AI Lakehouse means organizations get cutting-edge AI, high-octane analytics, and secure, open access-all in one shot-on the hyperscaler cloud of their choice. By wrapping a 'catalog of catalogs' around Iceberg and its Autonomous AI Database, Oracle is making it radically simpler for teams to discover, secure, and leverage data everywhere. It's a game-changer for breaking down barriers in today's fragmented data landscape."