Autonomous AI Database on Exadata Cloud@Customer

The simplest place to develop applications

Create modern, data-driven applications with any data, development style, and workload while automatically benefiting from high performance, consistent security models, and mission-critical capabilities.

Lowest adoption costs

Run Autonomous AI Database on VM clusters inside an existing Exadata Cloud@Customer with no setup costs, making it the easiest and least expensive way to start using the word's most advanced database in customer data centers.

Autonomous operations

Improve management efficiency and reduce costs by replacing error-prone manual management with machine learning–driven automation to patch, scale, tune, secure, back up, and repair databases.

Data residency and security

Secure Oracle databases behind customers’ data center firewalls to help meet data residency, security, and governance requirements.

High performance with pay-per-use economics

Automatic, online scaling of database consumption based on currently running database queries increases performance when needed and reduces costs at other times. The ability to overprovision CPUs for low-consumption users and set database consumption to zero when not in use further reduces costs.

Consolidate databases

Concurrently run autonomous and non-autonomous databases on the same Exadata Cloud@Customer, enabling organizations to efficiently consolidate all types of workloads and develop new database applications.

• Oracle brings the Autonomous AI Database to every data center
• Autonomous AI Database (PDF)
• Autonomous AI Database on Dedicated Exadata Infrastructure datasheet (PDF)
• Exadata Cloud@Customer
• Pricing

Converged database simplicity

Replace the complexity and risk of managing multiple single-purpose databases with one autonomously managed database that supports all data types, workloads, and development styles.

High performance

Run OLTP applications faster with SQL latency of less than 14 microseconds, up to 89 million SQL IOPS, and the automated database tuning and indexing capabilities of Autonomous AI Database.

High availability

Improve the availability of critical databases with built-in Real Application Clusters, redundant infrastructure, application continuity, and automated disaster recovery and backups.

Greater developer productivity

Enable developers to build enterprise and cloud native applications faster by avoiding the need to manually provision, tune, and scale databases.

Optimized workload consolidation

Use Autonomous AI Database on Exadata Cloud@Customer to run OLTP workloads, taking advantage of isolated VM clusters with customized amounts of compute, memory, and storage to optimize application performance and consolidation efficiency.

Lower costs

Run OLTP workloads with the lowest possible cloud consumption costs by automatically scaling resources up to meet peak demands and back down to minimize costs, all without interrupting operations.

Business-critical lakehouses made simple

Make it easy to store and analyze terabytes to petabytes of diverse information with less integration, tuning, and management using self-service data warehouses that include built-in high availability and security.

Built-in analytics

Accelerate data analysis with built-in machine learning, spatial, graph, and text analytics that eliminate the need to extract, transform, and load data into separate databases.

Scalable high-performance queries

Create automated data summaries, optimize queries, and automatically scale compute up to 3X for consistently fast query performance using optimized Exadata Cloud@Customer infrastructure with unique parallel query and analytics offload capabilities.

Converged data analytics

Analyze all data types including relational, graph, JSON, and spatial, as well as data in object storage-based data lakes.

Optimized workload consolidation

Use Autonomous AI Database Service on Exadata Cloud@Customer infrastructure for analytics workloads and take advantage of isolated VM clusters with customized amounts of compute, memory, and storage to optimize application performance and consolidation efficiency.

Lower costs

Run analytics workloads with the lowest possible cloud consumption costs by offloading IO and compute-intensive processing to Exadata storage servers, reducing management costs, and automatically scaling resources up and down to meet peak demands and minimize costs, all without interrupting operations.

• Analyst report: Extracting maximum value from your data with Oracle Autonomous AI Lakehouse (PDF)