Editing IBM Db2 (section)

===Db2 Warehouse on Cloud===
Formerly named "dashDB for Analytics", [https://www.ibm.com/cloud/db2-warehouse-on-cloud Db2 Warehouse on Cloud] is a fully managed, elastic, cloud data warehouse built for high-performance analytics and [[machine learning]] workloads.

Key features include:

* Autonomous cloud service: Db2 Warehouse on Cloud runs on an autonomous platform-as-a-service, and is powered by Db2's autonomous self-tuning engine. Day-to-day operations, including database monitoring, uptime checks and failovers, are fully automated. Operations are supplemented by a DevOps team that are on-call to handle unexpected system failures.
* Optimized for analytics: Db2 Warehouse on Cloud delivers high performance on complex analytics workloads by utilizing [[IBM BLU Acceleration]], a collection of technologies pioneered by [[IBM Research]] that features four key optimizations: (1) a columnar organized storage model, (2) in-memory processing, (3) querying of compressed data sets, and (4) data skipping.
* Manage highly concurrent workloads: Db2 Warehouse on Cloud includes an Adaptive Workload Management technology that automatically manages resources between concurrent workloads, given user-defined resource targets. This technology ensures stable and reliable performance when tackling highly concurrent workloads.
* Built-in machine learning and geospatial capabilities: Db2 Warehouse on Cloud comes with in-database machine learning capabilities that allow users to train and run machine learning models on Db2 Warehouse data without the need for data movement. Examples of algorithms include [[Association rule learning|Association Rules]], [[Analysis of variance|ANOVA]], [[K-means clustering|k-means]], [[Regression analysis|Regression]], and [[Naive Bayes classifier|Naïve Bayes]]. Db2 Warehouse on Cloud also supports spatial analytics with Esri compatibility, supporting Esri data types such as GML, and supports native Python drivers and native Db2 Python integration into Jupyter Notebooks. 
* Elasticity: Db2 Warehouse on Cloud offers independent scaling of storage and compute, so organizations can customize their data warehouses to meet the needs of their businesses. For example, customers can burst on compute during peak demand, and scale down when demand falls. Users can also expand storage capacity as their data volumes grow. Customers can scale their data warehouse through the Db2 Warehouse on Cloud web console or API. 
* Data security: Data is encrypted at-rest and in-motion by default. Administrators can also restrict access to sensitive data through data masking, row permissions, and role-based security, and can utilize database audit utilities to maintain audit trails for their data warehouse.
* [[Polyglot persistence]]: Db2 Warehouse on Cloud is optimized for polyglot persistence of data, and supports relational (columnar and row-oriented tables), geospatial, and [[NoSQL]] document ([[XML]], [[JSON]], [[BSON]]) models. All data is subject to advanced data compression.
* Deployable on multiple cloud providers: Db2 Warehouse on Cloud is currently deployable on [[IBM cloud computing|IBM Cloud]] and Amazon Web Services (AWS).