2/27/2024 0 Comments Redshift query cost![]() So, if you have no or very little engineering support to lean on, then BigQuery or Redshift serverless are better options. Redshift provides documentation for each step, but you may still require some engineering support to get these steps right. Redshift allows you to allocate resources manually (and also offers a serverless option).īefore you can load any customer data or write a single query on Redshift, you’ll first need to define node type, create clusters, configure databases, and manage cluster permissions. In general, however, Redshift is more cost effective for running regular queries or API calls used in daily marketing reports, while BigQuery is better for processing low-frequency workloads that deal with more complex schemas and resource-intensive queries made up of multiple joins or aggregates.īigQuery is a ready-to-use data warehouse that automatically scales infrastructure resources as needed. Use real data sets and queries from your marketing analytic operations and benchmark both warehouses to truly understand which is better for you.īenchmarking your live workloads is also one of the most useful ways to utilize the $300 of free credits that BigQuery offers and the 750 free hours per month offered by Redshift. To get a clear picture of what it will cost to run queries on your own datasets, it’s best to test both these platforms in your production environment. On top of that, factors like warehouse configuration, number of joins used, internal data schema, and data size can all impact the result. And secondly, your business workloads may differ from the TPC-DS one used in this study. Firstly, each warehouse has a different architecture that suits different workloads better than others. ![]() However, don’t let this benchmark result alone influence your final decision - it may not accurately reflect your needs for two reasons. BigQuery ran on a GCP server with 3,000 slots - costing $120.00 per hour.Įxecuting all 99 test queries on Redshift cost $110.73, while it cost $511.09 on BigQuery.Redshift ran on an AWS server that had 38 ra3.4xlarge nodes - costing $123.88 per hour.To ensure a level playing field, both data warehouses were set with comparable configurations and costs. The best runtime out of the three executions was used in the final result. A total of 99 different queries were executed on this data set, and each query was executed three times. The GigaOm benchmark study used an industry-standard TPC-DS data set that amounted to 30TB of data. But it’s worth doing a benchmark study with your own production environment data sets to find out which data warehouse delivers the best performance for your needs. The better your query performance, the faster and more cost effectively you’ll be able to find insights such as which user action led to the most conversions or which common user attributes correlate with better lifetime value.Īccording to a benchmark study by research firm GigaOm, Redshift outperformed BigQuery by nearly five times with respect to query execution time and cost.
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