Scientific Data Storage for Cloud Computing

Abstract:

Traditionally data storage used for geophysical software systems has centered on file-based systems and libraries such as NetCDF and HDF5. In contrast cloud based infrastructure providers such as Amazon AWS, Microsoft Azure, and the Google Cloud Platform generally provide storage technologies based on an object based storage service (for large binary objects) complemented by a database service (for small objects that can be represented as key-value pairs). These systems have been shown to be highly scalable, reliable, and cost effective. We will discuss a proposed system that leverages these cloud-based storage technologies to provide an API-compatible library for traditional NetCDF and HDF5 applications. This system will enable cloud storage suitable for geophysical applications that can scale up to petabytes of data and thousands of users. We’ll also cover other advantages of this system such as enhanced metadata search.