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Autonomous Database for analytics and data warehousing (ADW)

A fully automated cloud database service optimized for analytic workloads, including data marts, data warehouses, and data lakes. It is preconfigured with columnar format, partitioning, and large joins to simplify and accelerate database provisioning, extracting, loading, and transforming data; running sophisticated reports; generating predictions; and creating machine learning models. With Autonomous Database, data scientists, business analysts, and non-experts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built on Oracle Database and Oracle Exadata, Autonomous Database is available on Oracle Cloud Infrastructure for shared or dedicated deployments, and on-premises with Exadata Cloud@Customer and Dedicated Region Cloud@Customer.

Oracle Autonomous Database: Revolutionizing Data Management video

Oracle Autonomous Database: Revolutionizing Data Management (0:30)

Oracle Autonomous Data Warehouse Innovations Data Warehouse Innovations

Watch Andrew Mendelsohn, EVP of Database Server Technologies at Oracle discuss how Oracle is automating data management for all users.

Why Snowflake Melts When Compared to Autonomous Data WarehouseWhy Snowflake melts when compared to Autonomous Database

Detailed analysis by industry expert DSC illustrates why Oracle Autonomous Database for analytics and data warehousing is a better pick for the majority of global organizations.

Autonomous Data Warehouse compatible applications and tools Applications and tools compatible with Autonomous Database

Learn about applications and tools that are compatible with Autonomous Database for analytics and data warehousing.

5 reasons Why Oracle Autonomous Database for analytics and data warehousing is better.

Why choose Autonomous Database for analytics and data warehousing?

Autonomous warehouse management

Oracle Autonomous Database for analytics and data warehousing eliminates nearly all manual administrative tasks. It automates common tasks like backup, configuration, and patching. Uniquely, it continuously automates performance tuning and autoscaling, with no downtime, human intervention, or over-provisioning. This reduces administration effort by up to 90% and enables business teams to operate without help from IT.

The 2025 Imperative: Intelligent Automation Now

A complete solution with self-service data tools and analytics

Autonomous Database for analytics and data warehousing is the only complete solution that uses a converged database, providing built-in support for multimodel data and multiple workloads. It includes built-in self-service tools to improve the productivity of analysts, data scientists, and developers.

Autonomous for Business Success (PDF)

Available in Oracle public cloud or in customers’ data centers

Unlike other cloud data warehouse services, Autonomous Database for analytics and data warehousing offers three deployment choices.

Comprehensive data and privacy protection

Autonomous Database for analytics and data warehousing autonomously encrypts data at rest and in motion, protects regulated data, applies all security patches, and performs threat detection. In addition, customers can easily use Oracle Data Safe to conduct user and privilege analysis, sensitive data discovery, and protection, and activity auditing. Autonomous Database makes it easy to keep data safe from outsiders and insiders.

IDC Research: The Security Benefits of a Fully Managed Database Service (PDF)

Autonomous Database for analytics and data warehousing features

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 consistently high performance

Autonomous Database for analytics and data warehousing 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 Database for analytics and data warehousing 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

Self-service data management tools

Data tools provide a simple, self-service environment for loading data and making it available to their extended team for collaboration. Business and data analysts can easily load and transform data with drag-n-drop capabilities, generate business models, quickly discover anomalies, outliers and hidden patterns, understand data dependencies, and the impact of changes.

Features
  • Data loading
  • Data Transformation
  • Business Model
  • Data Insights
  • Catalog

Machine learning for everyone

Build and deploy machine learning models in Oracle Autonomous Database for analytics and data warehousing using scalable and optimized in-database algorithms. Oracle Machine Learning accelerates the creation of machine learning models for data scientists by eliminating the need to move data to dedicated machine learning systems.

Features
  • In-database algorithms
  • Automatic data preparation
  • AutoML automates model development
  • Easy model deployment through REST and SQL interfaces
  • High performance, scalability and security
  • Oracle Machine Learning Notebooks
  • OML for Python
  • OML Services
  • OML AutoML UI
  • Oracle Machine Learning for SQL

Uncover hidden relationships in data

Autonomous Database includes graph database features to represent and manage complex data relationships. The graph analytics enable data scientists and developers to apply pattern recognition, classification, and statistical analysis for deeper context.

Graph Studio key features:
  • Automated graph modeling
  • Automated install, upgrade, and provisioning
  • Autosave, backup, and checkpoint data restoration features
  • Advanced notebooks and visualization
  • Ability to schedule analysis
  • Sample notebooks and workflows for different use cases

Making sense of location

The spatial features in Autonomous Database for analytics and data warehousing 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

Get started with Oracle Autonomous Database for analytics and data warehousing for free.

See what top industry analysts are saying about Autonomous Database for analytics and data warehousing

IDC finds Autonomous Database  customers obtain a
417% ROI in five years

IDC finds Autonomous Database customers obtain a 417% ROI in five years.

Learn more
Wikibon finds Oracle Autonomous Database is 50% lower cost than AWS

Wikibon finds Oracle Autonomous Database is 50% lower cost than AWS.

Learn more (PDF)
KuppingerCole

KuppingerCole: Oracle Autonomous Database is ranked #1 overall for Cloud Database and Big Data security

Read the report (PDF)

See what’s new in Autonomous Database

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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Use cases for Autonomous Database for analytics and data warehousing

Improving analytics for the line of business

Deploy a self-service departmental data warehouse to consolidate multiple enterprise systems, spreadsheets, and third-party data sources into a trusted, maintainable, and integrated dashboard. Integrated self-service data tools allow users to load and transform data with drag and drop, generate business models, quickly discover anomalies, and build machine learning (ML) models.

See the reference architecture

Discover Oracle Departmental Data Warehouse

Improving analytics for the line of business
Answer complex questions using all data

Simplify and modernize an enterprise data warehouse

Answer more complex questions using all data. Simplify your enterprise data warehouse to support multimodal, converged data with autonomous capabilities.

See the reference architecture

Discover your enterprise data warehouse solution

Augment decision-making with machine learning

Build and deploy machine learning models in Oracle Autonomous Database for analytics and data warehousing using scalable and optimized in-database algorithms.

See the reference architecture

Discover your machine learning solution

Augment decision making with machine learning

Autonomous Database for analytics and data warehousing pricing

Autonomous Database for analytics and data warehousing on Shared Infrastructure

Product
Comparison Price (/vCPU) *
Unit price
Unit
Oracle Autonomous Data Warehouse


OCPU per hour
Oracle Autonomous Database – Exadata Storage


Terabytes Storage Capacity per month

Autonomous Database for analytics and data warehousing on Dedicated Infrastructure

Product
Comparison Price (/vCPU) *
Unit price
Unit
Oracle Autonomous Data Warehouse - Dedicated


OCPU per hour
Oracle Cloud Infrastructure - Database Exadata Infrastructure - Quarter Rack - X8M


Hosted environment per hour
Oracle Cloud Infrastructure - Database Exadata Infrastructure - Quarter Rack - X8


Hosted environment per hour
Oracle Cloud Infrastructure - Database Exadata Infrastructure - Half Rack - X8


Hosted environment per hour
Oracle Cloud Infrastructure - Database Exadata Infrastructure - Full Rack - X8


Hosted environment per hour
Oracle Cloud Infrastructure - Oracle Database Exadata Infrastructure - Quarter Rack - X7


Hosted environment per hour
Oracle Cloud Infrastructure - Database Exadata Infrastructure - Half Rack - X7


Hosted environment per hour
Oracle Cloud Infrastructure - Database Exadata Infrastructure - Full Rack - X7


Hosted environment per hour

  • For Autonomous Database for analytics and data warehousing on Dedicated Infrastructure:
  • – Minimum term for subscription to Database Exadata Infrastructure is 48 hours

Autonomous Database for analytics and data warehousing Bring Your Own License (BYOL)

Product
Comparison Price (/vCPU) *
Unit price
Unit
Oracle Autonomous Database for analytics and data warehousing


OCPU per hour
Oracle Autonomous Database for analytics and data warehousing - Dedicated


OCPU per hour

  • If you run Oracle Database Enterprise Edition and the required options listed below, your BYOL requirements are as follows:
  • – For each supported Processor license of Oracle Database Enterprise Edition plus the Multitenant Option, you may activate up to 2 OCPUs of the BYOL Cloud Service.
  • – Using a single BYOL Cloud Service instance of 17 OCPUs or more, including autoscale OCPUs, additionally requires one supported Processor license of the Real Application Clusters Option for every 2 OCPUs of the BYOL Cloud Service.
  • – Using Oracle Autonomous Data Guard with your Autonomous Data Warehouse BYOL service additionally requires one supported Processor license of the Active Data Guard Option for every 2 OCPUs of the BYOL Cloud Service.
  • – For every 25 supported Named User Plus licenses of Oracle Database Enterprise Edition plus the Multitenant Option, you may activate up to 2 OCPUs of the BYOL Cloud Service.
  • – Using a single BYOL Cloud Service instance of 17 OCPUs or more, including autoscale OCPUs, additionally requires 25 supported Named User Plus licenses of the Real Application Clusters Option for every 2 OCPUs of the BYOL Cloud Service.
  • – Using Oracle Autonomous Data Guard with your Autonomous Data Warehouse BYOL service additionally requires 25 supported Named User Plus licenses of the Active Data Guard Option for every 2 OCPUs of the BYOL Cloud Service.

  • If you run Oracle Database Standard Edition, Oracle Database Standard Edition One, or Oracle Database Standard Edition 2, then your BYOL requirements are as follows:
  • – For each supported Processor license of Oracle Database Standard Edition programs (where a Processor is defined as equivalent to an occupied socket), you may activate up to 4 OCPUs of the BYOL Cloud Service.
  • – For every 10 supported Named User Plus licenses of Oracle Database Standard Edition programs, you may activate 1 OCPU of the BYOL Cloud Service.
  • – For every 10 supported Application User licenses of Oracle Technology Foundation for JD Edwards EnterpriseOne, you may activate 1 OCPU of the BYOL Cloud Service.
  • – Using Oracle Autonomous Data Guard doesn’t require the Active Data Guard Option.
  • – Each Oracle Autonomous Data Warehouse BYOL service instance may not exceed 8 OCPUs, including autoscale OCPUs. The aggregate of all Oracle Autonomous Data Warehouse BYOL service instances may exceed this limit.

*To make it easier to compare pricing across cloud service providers, Oracle web pages show both vCPU (virtual CPUs) prices and OCPU (Oracle CPU) prices for products with compute-based pricing. The products themselves, provisioning in the portal, billing, etc. continue to use OCPU (Oracle CPU) units. OCPUs represent physical CPU cores. Most CPU architectures, including x86, execute two threads per physical core, so 1 OCPU is the equivalent of 2 vCPUs for x86-based compute. The per-hour OCPU rate customers are billed at is therefore twice the vCPU price since they receive two vCPUs of compute power for each OCPU, unless it’s a sub-core instance such as preemptible instances. Additional details supporting the difference between OCPU vs. vCPU can be accessed here.

October 13, 2021

Autonomous Database enhances data lake analytics

Martin Gubar, Director of Product Management

Oracle data warehouses have been a mainstay in data architectures for decades. For good reason—data warehouses are scalable, highly secure, handle complex queries with high levels of concurrency, and are available to a wide range of tools and applications. With that said, data lakes have increasingly become a key part of data platforms.

Read the complete post

Resources

Documentation

Autonomous Database for analytics and data warehousing documentation

Product documentation and help center to deploy Autonomous Database for analytics and data warehousing for shared and dedicated infrastructure.

Additional information

Cloud Learning
related content

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

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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.