PERFORMANCE BENCHMARKING OF MODERN CLOUD DATA WAREHOUSES: SNOWFLAKE, BIGQUERY, AND REDSHIFT

Cloud computing and big data technologies have evolved rapidly, with significant effects on enterprise data
management and analytical data processing. The contemporary cloud data warehouses offer scalable, highperformance solutions that enable organizations to handle vast amounts of structured and semi-structured data and
support advanced analytics and business intelligence applications. The most popular services in this area will be
Snowflake, Google BigQuery, and Amazon Redshift, each with its own architecture, scaling profile, and optimization
strategies. Infrastructure and data strategy decisions have become increasingly important as more analytical workloads
move to the cloud, and to make informed choices, it is imperative to assess the performance capabilities of these
platforms.
In this paper, we provide a comparative performance benchmark analysis of three popular cloud data warehouse
systems: Snowflake, Google BigQuery, and Amazon Redshift. The study analyses the most important performance
metrics, including time to query execution, scalability, resource consumption, and cost-performance, under normal
analytical workloads. The study assesses the effects of architectural characteristics of serverless computing, distributed
query processing, and storage-compute separation on system performance, using standardized benchmarking
scenarios to simulate enterprise analytics.
The results emphasize the advantages and disadvantages of each platform under different workload conditions and
show the impact of architectural differences on analytical performance and scalability. The findings provide
information to help the organization choose the right cloud data warehouse solutions to support its data-intensive
workloads. Finally, the research has contributed to the growing literature on cloud-based data analytics infrastructure
and has provided useful guidance to enterprise data architects, analytics engineers, and cloud infrastructure decisionmakers.