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Oracle Autonomous Data Warehouse

Oracle Autonomous Data Warehouse is a cloud data warehouse service that eliminates virtually all the complexities of operating a data warehouse, securing data, and developing data-driven applications. It automates provisioning, configuring, securing, tuning, scaling, patching, backing up, and repairing of the data warehouse. Unlike other fully managed cloud data warehouse solutions that only patch and update the service, it features elastic, automated scaling, performance tuning, security, and a broad set of built-in converged database capabilities that enable simpler queries across multiple data types, machine learning analysis, simple data loading, and data visualizations. It’s available in both the Oracle public cloud and customers data centers with Oracle Cloud@Customer.

Oracle Autonomous Data Warehouse
Autonomous Data Warehouse introduction

Watch how Oracle Autonomous Data Warehouse can help departments use analytics to get more value from any data.

Autonomous Data Warehouse pricing

Learn about Autonomous Data Warehouse pricing.

Why choose Oracle Autonomous Data Warehouse?

Automated data warehouse management

Autonomous Data Warehouse intelligently automates provisioning, configuring, securing, tuning, and scaling a data warehouse. This eliminates nearly all the manual and complex tasks that can introduce human error. Autonomous management will enable customers to run a high-performance, highly available, and secure data warehouse while reducing administrative costs.

Unior Group, based in Zreče, Slovenia, manage 85 million records with no database administrators. (1:23)

Watch the Autonomous Database video (1:00)

The 2025 Imperative: Intelligent Automation Now (PDF)
Automated data warehouse management

A complete solution with built-in analytics

Autonomous Data Warehouse is the only complete solution that uses a converged database providing built-in support for multimodel data and multiple workloads such as analytical SQL, machine learning, graph, and spatial. It requires no integration with other services, making it easy to load any data, run complex queries across multiple data types, build sophisticated analytical models, visualize information, deliver dashboards and develop data-driven applications.

Maxim’s Caterers, based in Hong Kong, analyzes 600,000 daily transactions and social media data using ad-hoc queries and what-if analysis to improve business efficiency and competitiveness.

Autonomous for Business Success (PDF)
A complete solution with built-in analytics

Consistent high performance for any number of concurrent users

Autonomous Data Warehouse uses continuous query optimization, table indexing, data summaries, and auto-tuning to ensure consistent high performance even as data volume and number of users grows. Autonomous scaling can temporarily increase compute and I/O by a factor of three to maintain performance. Unlike other cloud services which require downtime to scale, Autonomous Data Warehouse scales while the service continues to run.

Vodafone Fiji saw a 6X improvement for the processing of 600 million records per day. (1:27)

Pique Solutions: Cloud Data Warehousing Platforms (PDF)
Consistent high performance for any number of concurrent users

Comprehensive data and privacy protection

Autonomous Data Warehouse makes it easy to keep data safe from outsiders and insiders. It autonomously encrypts data at rest and in motion (including backups and network connections), protects regulated data, applies all security patches, enables auditing, and performs threat detection. In addition, customers can easily use Oracle Data Safe to conduct ongoing security assessments, user and privilege analysis, sensitive data discovery, sensitive data protection, and activity auditing. Autonomous Data Warehouse protects the organization and all data against data breaches, malware injections, DDoS attacks, malicious insiders, advanced persistent threats, insecure APIs, account hijacking, and more.

DX Marketing, based in Savannah, Georgia, relies on Autonomous Data Warehouse to protect more than 260 million licensed records of US consumers and their associated private information. (1:54)

IDC Research: The Security Benefits of a Fully Managed Database Service (PDF)
Comprehensive data and privacy protection

Available in Oracle public cloud or in customers’ data centers

Unlike other cloud data warehouse services, Autonomous Data Warehouse offers three deployment choices.

  • Shared infrastructure (public cloud):

    With the shared infrastructure deployment option, customers get the benefits of automated operations, performance, scale, and the advanced security of Autonomous Data Warehouse running in Oracle public cloud, but for a lower cost.
  • Dedicated infrastructure (public cloud):

    The dedicated infrastructure deployment option provisions customer databases on dedicated Exadata infrastructure in Oracle public cloud. Dedicated infrastructure provides isolation from other users and gives the same performance and predictability as on-premises deployments. Additionally, customers have the ability to control autonomous operational policies, such as the timing of upgrades and patches.
  • Cloud@Customer infrastructure (customer’s data center):

    Autonomous Data Warehouse on Exadata Cloud@Customer combines all the benefits of having Exadata Database Machines in customer data centers with the added simplicity of autonomous cloud management. The service enables self-service agility, removes the challenge of lifting and shifting data warehouses to the public cloud, and allows customers to meet organizational requirements for strict data sovereignty and security, since Cloud@Customer runs in the customer’s data center.
WinterCorp Research Note: Managed Cloud Database Deployment Options are Growing (PDF)
Available in Oracle public cloud or in customers’ data centers

Autonomous Data Warehouse

Simplified data warehouse management—with autonomous administration

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 will enable customers to run a high-performance, highly available, and secure data warehouse while reducing administrative costs.

Features
  • Auto-scaling
  • Auto-securing
  • Auto-tuning
  • Auto-backups
  • Auto-repairing
  • Auto-patching

Ensure consistent high performance

Autonomous Data Warehouse continuously monitors all aspects of system performance. It makes adjustments autonomously to ensure consistent high performance even as workloads, query types, and number of users vary.

Features
  • Auto-scaling
  • Auto-tuning
  • Auto-indexing
  • Hybrid Columnar Compression
  • Columnar processing
  • Smart Scan
  • Automatic optimizer statistics gathering

Reduce risk with database security

Secure Autonomous Data Warehouse 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.

Features
  • Transparent data encryption
  • Encryption key management
  • Privileged user and multifactor access control
  • Data classification and discovery
  • Database activity monitoring and blocking
  • Consolidated auditing and reporting
  • Data masking
  • Data redaction

Bring algorithms to your data

Oracle Machine Learning embeds more than 30 high-performance, parallelized machine learning algorithms in Autonomous Data Warehouse. Bringing the algorithms to the data minimizes data movement, preserves data security, and accelerates model development and deployment.

Features
  • Scalable data exploration
  • Automated data preparation
  • Automated data sampling
  • Automated partition model ensembles
  • 30+ in-database high-performance algorithms
  • Automatic algorithm, feature selection, and model tuning
  • Choice of interfaces and APIs

Uncover hidden relationships in data

Graphs enable users to model, explore, and analyze data based on how it’s related to other information. They enable new insights into data based on connections between data entities in a variety of applications such as social media, online payments, personnel records, linked open data, and more.

Features
  • Property and RDF graphs
  • In-memory graph server (PGX)
  • PGQL and SPARQL graph query languages
  • 50+ graph algorithms
  • Support for graph visualization

Making sense of location

The spatial features in Autonomous Data Warehouse address all forms of applications, spatial workloads, and datasets including the most demanding, large-scale location intelligence and geospatial applications.

Features
  • Data model and comprehensive analytics for 2D spatial data
  • High performance, parallel spatial processing
  • Standards-based SQL and Java APIs
  • Native JSON and REST support
  • Location tracking server
  • Contact tracing built-in functions
  • Self-service Spatial Studio

View all Autonomous Database customer successes

An economical, efficient, and effortless customer experience

Learn how Oracle customers are using Oracle Autonomous Database to transform their businesses by redefining data warehousing through machine learning and automation

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“We now have a scalable, low-cost cloud platform to power our business.”

Use cases for Autonomous Data Warehouse

  • Build a departmental data warehouse

    Deploy a self-service departmental data warehouse to consolidate data from multiple spreadsheets and other flat-file data sources into a trusted, maintainable, and high-quality dashboards.

    See the reference architecture

  • Build a departmental data warehouse for enterprise applications

    Consolidate data from multiple enterprise systems, spreadsheets, and 3rd party data sources into an integrated and analytical data store.

    See the reference architecture

  • Extend an enterprise data warehouse

    Simplify your enterprise data warehouse to support multimodel, converged data with autonomous capabilities.

    See the reference architecture

  • Build an enterprise data warehouse with integrated data lake

    Combine the abilities of a data lake and a data warehouse to manage any data type for business analysis and machine learning.

    See the reference architecture

View all Autonomous Data Warehouse architecture patterns

Use cases for Autonomous Data Warehouse
October 31, 2019

Oracle Autonomous Data Warehouse: The world’s first and only self-securing database cloud service

Bill Kleyman, Executive Vice President of Digital Solutions, Switch | Industry Influencer

So, what makes working with the Oracle Autonomous Data Warehouse solution so unique? Based on my observations, it’s the security aspect. The security is built into the DNA of the entire architecture. I’ll explain how.

Read the complete post

Resources

Documentation

Autonomous Data Warehouse documentation

Product documentation and help center to deploy Autonomous Data Warehouse service for shared and dedicated infrastructure.

Additional information

Cloud Learning
related content

Newsletters

Information, tips, tricks, and sample code for an autonomous, cloud-driven world.

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