Project Daytona is designed to support a wide class of data analytics and machine learning algorithms. The project, code-named Daytona, is built on Windows Azure and employs the available Windows Azure compute and data services to offer a scalable and high-performance system for data analytics. Project Daytona is part of an active research and development project in the eXtreme Computing Group of Microsoft Research and made its debut at the Microsoft Research Faculty Summit last week.
Researchers in a wide range of domains, such as healthcare, education, and environmental science, have large and growing data collections, and they need simple tools to help them find signals in their data and uncover insights. Project Dayton is available, as a free download, so that researchers can use it to set up their own large-scale, cloud data-analysis service on Windows Azure. Almost any application that involves data manipulation and analysis can take advantage of Project Daytona. Project Daytona explores a specific use case: Data analytics as a service on Windows Azure.
Project Daytona is designed for the cloud, specifically for Windows Azure and for cloud storage services. It consumes data with minimum overhead and with the ability to recover from failures. Project Daytona is horizontally scalable and elastic. This allows you to focus on your data exploration without having to worry about acquiring compute capacity or time-consuming hardware setup and management. Since algorithms in data analytics and machine learning are often iterative, Project Daytona provides support for iterative computations in its core runtime.
The current release of Project Daytona is a research technology preview (RTP). The team continues to tune the performance of Project Daytona and work on adding new functionality.