Introduction
Data analytics has revolutionized decision-making processes for businesses of all sizes. With technology advancements in cloud computing, data analytics tools have become more affordable and accessible to both small and large businesses. AWS Redshift and GCP BigQuery are two of the most popular cloud-based data warehousing solutions, both offering robust data analytics capabilities. However, businesses need to understand the cost implications of choosing either of these solutions. In this blog post, we'll be comparing the costs of AWS Redshift and GCP BigQuery for data analytics.
AWS Redshift vs GCP BigQuery Cost Comparison
For this comparison, we'll be using US-East (N. Virginia) as the AWS region and US (Iowa) as the GCP region. We'll be comparing the costs of using both solutions for one year (based on hourly usage).
AWS Redshift
AWS Redshift offers two pricing models; on-demand and reserved instances. The on-demand pricing model charges $0.25 per hour for a single-node cluster and $0.85 per hour for an eight-node cluster. The reserved instances pricing model offers a significant discount on the on-demand model with a one-year term. For example, a one-year reserved instance with a single-node cluster costs $0.15 per hour, while an eight-node cluster costs $0.45 per hour.
GCP BigQuery
GCP BigQuery offers both on-demand and flat-rate pricing models. The on-demand pricing model charges $5 per terabyte (TB) of data processed. The flat-rate pricing model offers a predictable cost for a committed data processing volume. The price for a flat-rate plan is $40,000 per month for 2,000 slots dedicated to processing data.
Conclusion
When it comes to cost comparison for data analytics between AWS Redshift and GCP BigQuery, GCP BigQuery has a slight edge due to its flat-rate pricing model. If your business is processing large volumes of data, a flat-rate price point with a dedicated processing volume can offer a better deal.