Architecting Cloud-Agnostic Data Solutions using Starburst for Multi-Vendor Integration

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.

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Publication Details

Journal
International Journal for Research Publication and Seminars
Published
2025-03-15
DOI
https://doi.org/10.36676/jrps.v16.i1.138
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Architecting Cloud-Agnostic Data Solutions using Starburst for Multi-Vendor Integration

Bharath Thandalam Rajasekaran, Dr Shantanu Bindewari
International Journal for Research Publication and Seminars
Big Data and Business Intelligence
article

Architecting Cloud-Agnostic Data Solutions using Starburst for Multi-Vendor Integration

Bharath Thandalam Rajasekaran, Dr Shantanu Bindewari
article en

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.

International Journal for Research Publication and SeminarsVol. 16(1)
Noida International University (IN), University of Maryland, College Park (US)
Openalex Percentile: Top 89%
Big Data and Business Intelligence
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