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Autonomous Data Warehouse

Oracle Autonomous Data Warehouse is the world’s first and only autonomous database optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built for the cloud and optimized using Oracle Exadata, Autonomous Data Warehouse benefits from faster performance and, according to an IDC report (PDF), lowers operational costs by an average of 63%.

Oracle Autonomous Database: Revolutionizing Data Management video

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

Introducing Oracle Database Service for Microsoft Azure

Larry Ellison and Satya Nadella have launched Oracle Database Service for Microsoft Azure, bringing the enterprise-grade performance, availability, and automation of Oracle Database to Azure customers.

Why choose Autonomous Data Warehouse?

Oracle is the only cloud provider that runs entirely on its own cloud (infrastructure, database, and applications cloud).

Applications and tools compatible with Oracle Autonomous Database

Learn about applications and tools that are compatible with Autonomous Database.

Get more value from data and analytics

Do more using a data platform designed for speed, agility, and simplicity

Autonomous Database provides the foundation for a data lakehouse—a modern, open architecture that enables you to store, analyze, and understand all your data. The data lakehouse combines the power and richness of data warehouses with the breadth, flexibility, and low cost of popular open source data lake technologies. Access your data lakehouse through Autonomous Database using the world's most powerful and open SQL processing engine.


Data lakehouse foundation diagramOracle’s data lakehouse platform is built from a combination of a data lake and data warehouse to form a data lakehouse. It merges data warehouse and data lake capabilities to enable easier data movement with a more unified architecture. Integrating data lake and data warehouse provides many benefits, including data management, AI and machine learning, and integration options.

Analyze any data, anywhere

Autonomous Database's advanced data processing engine lets you gain insights across multicloud data sources. It doesn't matter if your data is in AWS, Azure, Google Cloud Platform, or Oracle Cloud Infrastructure object stores and databases. Or, if your data is in big data file formats such as Apache Parquet, JSON, Apache ORC, Apache Avro, CSV, or XML, Autonomous Database delivers a simple, consistent view of your data estate using your preferred SQL-based tools and applications.


Manage all data services diagramAll the data ingestion, transformation and integration flows into the data stores, warehouses, and data lakes. At the very core, Oracle offers a unified, efficient, low cost and scalable place to unify all this enterprise data even though the data may sit unstructured all the way to structured and curated data. Here you can store, manage, analyze and understand all your data.

Empower innovators with integrated, self-service analytics

Increase the productivity of business users by reducing their dependency on IT, using self-service data tools, and creating low-code analytic applications. Enhance collaboration across teams with Autonomous Database’s analytic views that provide common business definitions and metrics integrated with Oracle Analytics Cloud, Tableau, and other business intelligence applications. Enhance business storytelling based on all data, using the power of built-in machine learning, spatial and graph analytics, and data visualization.


Self-service analytics diagramWith Oracle 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.

Prevent risks with security assessments, auditing, and active protection

Autonomous Database provides the most advanced data security that helps reduce the risk of a data breach and simplifies regulatory compliance. Its automated self-patching, automatic, always-on encryption and key management, granular access controls, and flexible data masking provide comprehensive user behavior monitoring with sophisticated auditing capabilities.


Advanced data security diagramEvaluate the security posture of your database and receive recommendations on how to migrate potential risks.

Autonomous Data Warehouse features

A modern data platform for business insights

Oracle Autonomous Database plays a central role in the data lakehouse as both an analytic engine and optimized data store. Users can access the lakehouse through Autonomous Database’s powerful and open SQL processing engine. Analyze Autonomous Database data from big data frameworks using highly efficient Apache Spark and Python connectivity.


Simplified data warehouse management—with built-in automation

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 enables customers to run a high-performance, highly available, and secure data warehouse while running thousands of databases with no administration.

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

Ensure consistently high performance

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

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
  • Data masking
  • Data redaction
  • Database activity monitoring and blocking
  • Consolidated auditing and reporting

Self-service data management tools

Data tools provide a simple, self-service environment for loading data and making it available for collaboration among extended teams. Business and data analysts can easily load and transform data with drag-and-drop capabilities; generate business models; quickly discover anomalies, outliers, and hidden patterns; and 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 Data Warehouse 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
  • Automatic data preparation
  • AutoML automates model development
  • Easy model deployment through REST and SQL interfaces
  • High performance, scalability, and security
  • In-database algorithms
  • Oracle Machine Learning services
  • Oracle Machine Learning AutoML User Interface
  • Oracle Machine Learning Notebooks
  • Oracle Machine Learning for Python
  • 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
  • Ability to schedule analysis
  • Advanced notebooks and visualization
  • Automated graph modeling
  • Automated install, upgrade, and provisioning
  • Autosave, backup, and checkpoint data restoration features
  • Sample notebooks and workflows for different use cases

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 modeling 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

Improve the availability of data warehousing and analytics workloads

Autonomous Database provides more than 99.995% availability1 with built-in Oracle Real Application Clusters, parallel infrastructure, automated disaster recovery, and backups.

Features
  • Automatic storage management
  • Maximum availability architecture
  • Oracle Active Data Guard
  • Oracle Autonomous Health Framework
  • Oracle Real Application Clusters
  • Oracle Data Safe

Get more timely analytics with accelerators for E-Business Suite, Fusion, and NetSuite

Oracle application accelerators for Oracle’s E-Business Suite, Fusion Applications, and NetSuite provide enhanced analytical capabilities with self-service data discovery, built-in ETL, and KPI metrics. Users can do more with comprehensive data integration and ready-to-use data models.

Features
  • Oracle application accelerators offer prebuilt ETL, enabling users to quickly create data warehouses from Oracle E-Business Suite data.
  • Oracle Fusion Analytics Warehouse and Oracle NetSuite Analytics Warehouse are built on Autonomous Database and provide an end-to-end cloud data warehouse and analytical solution.
  • For custom-built data warehouses, Autonomous Data Warehouse provides comprehensive data transformation flows that connect to Oracle and third-party applications.

See what’s new in Autonomous Database

See what top industry analysts are saying about Autonomous Data Warehouse

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

Learn more

Get started with Oracle Autonomous Data Warehouse for free

View all Autonomous Database customer successes

An economical, efficient, and effortless customer experience

Learn how Oracle customers are using Oracle Autonomous Data Warehouse to modernize their businesses through data lakes, machine learning, and automation.

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Autonomous Data Warehouse pricing

Autonomous Data Warehouse 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 Data Warehouse on Dedicated Infrastructure

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


OCPU per hour
Exadata Cloud Infrastructure—Quarter Rack—X9M


Hosted environment per hour
Exadata Cloud Infrastructure—Database Server—X9M


Hosted environment per hour
Exadata Cloud Infrastructure—Storage Server—X9M


Hosted environment per hour
Oracle Cloud Infrastructure—Oracle Database Exadata Infrastructure—Database Server—X8M


Hosted environment per hour
Oracle Cloud Infrastructure—Oracle Database Exadata Infrastructure—Storage Server—X8M


Hosted environment per hour

  • For Autonomous Data Warehouse on Dedicated Infrastructure, the minimum term for a subscription to Database Exadata Infrastructure is 48 hours.

Autonomous Data Warehouse Bring Your Own License

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


OCPU per hour
Oracle Autonomous Data Warehouse—Dedicated


OCPU per hour

*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) prices. OCPUs represent physical CPU cores. Most CPU architectures, including x86, execute two threads per physical core, so one OCPU is the equivalent of two 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.

July 20, 2022

Oracle Database Service for Microsoft Azure

Dave McCarthy, Research Vice President, Cloud and Edge Infrastructure Services, IDC

Oracle and Microsoft simplify the path to multicloud choice
Cloud has fundamentally changed the way organizations develop applications, secure data, and manage infrastructure. The ability to quickly provision resources, scale on demand, and deploy globally has created new opportunities to innovate. In 2022, IDC expects spending on cloud infrastructure to outpace non-cloud infrastructure for the first time.

Read the complete post

Resources

Documentation

Autonomous Data Warehouse documentation

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

  • Free step-by-step workshop
    Learn how to create a modern data warehouse, set up a data lake, or experiment with machine learning using a hands-on workshop with step-by-step instructions.
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1. The service level agreement (SLA) for 99.995% availability assumes the use of Oracle Autonomous Data Guard. The SLA is 99.95% availability when Autonomous Data Guard isn’t enabled.

2. 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.