Oracle has launched a fresh data lakehouse that aims to give businesses more freedom when managing their data. This new platform, called Autonomous AI Lakehouse, is designed to work smoothly across different clouds and on-premises systems. It supports Apache Iceberg, a popular open table format, to help companies improve how they analyze data and share it across various environments.

Many companies are turning to data lakehouses because they combine the affordability and scalability of data lakes with the fast performance of data warehouses. Oracle’s latest offering builds on existing services like Autonomous Database, Autonomous Data Warehouse, and Select AI. It introduces new features such as support for Apache Iceberg, a query accelerator, a new catalog called the Autonomous AI Data Catalog, and plug-and-play SQL support. These tools are meant to make data management easier and more flexible.

Moving Toward More Open and Interoperable Data Platforms

The addition of Iceberg support and a unified data catalog signals a shift in Oracle’s approach. Instead of sticking to a single cloud, Oracle is now embracing a more open, vendor-neutral strategy. This means it’s easier for businesses to connect Oracle’s tools with other cloud platforms like AWS, Google Cloud, and Azure. The new features allow seamless integration with popular data catalogs such as Databricks Unity, AWS Glue, and Snowflake Polaris.

Industry analysts say this move is a smart one. It makes Oracle’s platform more appealing to existing customers who want to keep using their current tools while gaining more flexibility. It also aligns Oracle with competitors like Microsoft and Google, who already offer open, multi-cloud data solutions. Oracle is recognizing that to stay competitive, it needs to support a variety of environments and avoid locking customers into a single cloud.

Focus on Efficiency, Cost Savings, and AI Integration

Oracle’s new lakehouse isn’t just about flexibility. It also aims to help companies work faster and save money. One feature called the Data Lake Accelerator dynamically adjusts compute and network resources based on how much data is being queried. This means businesses only pay for what they use, cutting down waste. Early testers have seen faster query times and better workload management, similar to what’s offered by platforms like Snowflake or Databricks.

Another cost-saving feature is the Exadata Table Cache. It stores frequently accessed data in high-speed flash storage, speeding up queries and reducing costs, especially for mixed on-premises and cloud setups. Additionally, Oracle has introduced GoldenGate for Iceberg, which streams real-time data into Iceberg tables, reducing the need for batch processing and making data updates quicker.

Beyond data management, Oracle has integrated AI capabilities directly into the lakehouse. It offers two main AI agents: the Select AI Agent and the Data Science Agent. The Select AI Agent helps businesses build and manage AI workflows within the platform, supporting various tools and automations. Meanwhile, the Data Science Agent allows data teams to explore data and generate insights using natural language, making AI more accessible and easier to use.

Oracle has made the Autonomous AI Lakehouse generally available to customers. Pricing depends on how many services a company uses, giving flexibility based on individual needs.

In summary, Oracle’s new lakehouse platform is designed to be flexible, cost-efficient, and ready for the future of data and AI. By supporting multiple clouds and offering advanced features, Oracle is positioning itself to compete more effectively in the evolving enterprise data landscape.

Inspired by

• https://www.infoworld.com/article/4072017/oracle-debuts-iceberg-compatible-autonomous-ai-lakehouse-to-boost-enterprise-analytics.html

Sources

• gmpg.org
• oracle.com
• moorinsightsstrategy.com
• constellationr.com
• cio.com