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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.
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.The 2025 Imperative: Intelligent Automation Now (PDF)
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.Autonomous for Business Success (PDF)
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.Pique Solutions: Cloud Data Warehousing Platforms (PDF)
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.IDC Research: The Security Benefits of a Fully Managed Database Service (PDF)
Unlike other cloud data warehouse services, Autonomous Data Warehouse offers three deployment choices.
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.
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.
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.
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.
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.
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.
Learn how Oracle customers are using Oracle Autonomous Database to transform their businesses by redefining data warehousing through machine learning and automation
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.
Consolidate data from multiple enterprise systems, spreadsheets, and 3rd party data sources into an integrated and analytical data store.
Simplify your enterprise data warehouse to support multimodel, converged data with autonomous capabilities.
Combine the abilities of a data lake and a data warehouse to manage any data type for business analysis and machine learning.
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