Complimentary Analyst Report

How Does Using a Semantic Layer Impact Cloud Data Warehouse Performance?

See how your cloud data warehouse performs with and without a semantic layer at scale

What is the impact on query performance, user concurrency and costs associated with running large-scale analytics on your cloud data warehouse(s) using a semantic layer?

Cloud Data Warehouse Performance Benchmark Reports AtScale

To answer these questions, we set out to test the performance and scalability boundaries of the most popular cloud data warehouses at a 10 TB scale factor (28+ billion rows). This represents a reasonable real-life analytics schema and set of queries for a large business.

Amazon Redshift

Azure Synapse Analytics SQL

Google BigQuery

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These benchmark reports provide quantified results for each cloud data warehouse and detailed information on the impact of a using a semantic layer at scale on:

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What We Learned

Our tests proved that the inclusion a semantic layer improves cloud data warehouses by:

  1. Increasing query performance
  2. Improving user concurrency
  3. Reducing costs
  4. Drastically simplifying queries for users
  5. Ensuring all users access the same, secure data

Want to see for yourself?

Download the Cloud Data Warehouse Performance Benchmark Reports to see how the top industry players perform with and without a semantic layer in place:

Amazon Redshift

Azure Synapse Analytics SQL

Google BigQuery

Snowflake