Spatial Big Data (SBD) is at the core of the Geographic Information Systems (GIS) that use location-indexed geographic data to solve problems in many fields, including retail, banking, healthcare, agriculture, and the environmental field to name just a few.
SBD aligns with the three fundamental “V”s associated with big data: variety, volume, and velocity. SBD is diverse, comprising raster data, such as satellite or drone images, vector data such as GPS data, and graph data, such as electric grids or road networks. And with the advent of IoT sensors as well as open-source—even crowdsourced—SBD repositories, the quantity and the speed at which SPD are generated are accelerating dramatically.
Legacy GIS tools deployed in on-premises data centers can be both expensive and difficult to scale to meet accelerated SBD storage, mobility, and analysis demands. Thus, GIS has begun its journey to cloud infrastructures, driven by a number of value propositions such as cloud scalability and economics, better team collaboration, more efficient workflows, shared open data that is both accessible and secure, and greater public engagement.
This blog post discusses the challenges of cloud-based GIS and shows how Cloud Volumes ONTAP helps meet those challenges, including a hands-on case study.
A Geographic Information System captures, stores, manipulates, manages, and analyzes geospatial information, i.e., geographic data that are indexed by location and often by timestamp as well. The results of GIS queries and analyses are typically visualized as maps. GIS has many problem-solving and decision-making applications, from choosing optimal new store locations to modeling climate change and identifying crime patterns.
Despite the emergence of next-generation cloud-native GIS applications—including GIS-as-a- Service offerings such as cloud-based online mapping tools—the most common uses of the cloud for GIS are still cloud file sharing and data storage. However, the volume, variety and velocity of SBD as described above create a whole new set of GIS cloud challenges:
NetApp’s Cloud Volumes ONTAP is an enterprise-grade software-defined data storage management system that runs on the AWS, Azure, and Google public clouds. Let’s see how one company was able to use Cloud Volumes ONTAP in their GIS deployment.
This company wanted to use a cloud drive to save the output files from a Geospatial Information System, where each query results in hundreds of output files, some of which can be 25+ GB. They were faced with three major challenges:
Running Cloud Volumes ONTAP as an instance on AWS, the customer was able to implement a robust and cost-effective cloud file-sharing solution. Here are the highlights:
Cloud Volumes ONTAP has strong value propositions for any application that deals with big data, and that includes Geospatial Information Systems. Cloud Volumes ONTAP users significantly reduce their cloud spend with highly efficient data storage while maintaining uncompromising levels of data protection and business continuity. No matter how complex the company’s infrastructure, Cloud Volumes ONTAP provides a centralized point of data storage visibility and control.