Analytic databases are used by data-driven organisations to load, store, and analyze large amounts of data quickly in order to extract timely insights. Data volumes are rapidly increasing in modern organizations' information ecosystems, putting significant performance demands on legacy architectures. Businesses today need modern scalable architectures, high levels of performance and reliability and timely strategic insights to fully harness their data and gain a competitive advantage. Simultaneously, many businesses are moving to fully operated cloud services. Companies can use powerful data systems without the technological debt or the pressure of finding talent to handle the resources and architecture in-house with these controlled as-a-service implementation models. Users can pay as they go for these models, and set up a fully functioning analytical framework in the cloud with only a few clicks.

This study compares Actian Avalanche Cloud Data Warehouse, Amazon Redshift, Microsoft Azure Synapse, Google BigQuery, and Snowflake Data Warehouse using a GigaOm Analytic Field Test derived from the industry standard TPC Benchmark™ H (TPC-H)1.

This experiment yielded some intriguing findings, revealing some of the five platforms' efficiency characteristics. To learn more, download now.