Year: 2025
Type: article
Abstract: This abstract presents a new approach to architecting cloud-agnostic data solutions with Starburst to enable effortless integration on a range of vendor platforms. In today's fluid data landscape, organizations are turning to multiple cloud environments to process and analyze massive levels of information. This solution meets the imperative of interoperability and scalability, making data available and consistent across underlying infrastructure. Starburst's high-performance query engine is a critical enabler by consolidating disparate systems, reducing complexity, and maximizing performance. The method outlined centers on modular design practices and standardization approaches, which collectively provide robust, vendor-agnostic data architectures. This framework not only enhances operational flexibility and cost benefits but also allows enterprises to respond rapidly to evolving business needs without the perils of vendor lock-in.
Institution: University of Maryland, College Park
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409350449