Snowflake Query Cost Optimization

Snowflake Query Cost Optimization

Snowflake query cost optimization is challenging due to Snowflake’s pricing model. Snowflake provides a secure and scalable database engine with a unique architecture that decouples compute and storage resources, allowing you to pay only for the resources you use. Snowflake’s pay-as-you go pricing model does not require upfront costs for licenses or any hardware to purchase. There are no costs for infrastructure management and maintenance. You just pay for storage and compute as you go

Snowflake offers a scalable solution, but your cost can also scale to very unpleasant levels. Companies that do not optimize their Data Cloud costs are missing out on opportunities to drive more value from their data cloud investment. 

Getting More Value from the Snowflake Data Cloud

Modern cloud computing services such as the Snowflake Data Cloud make it easy for users to develop and scale data-intensive applications. But if you don’t effectively manage your data cloud environment, small mistakes and sub-optimal resource allocations can snowball into an avalanche of unexpected cloud costs. Snowflake’s pricing model, “it just works” manageability and the fact that it is a shared resource across an organization also means costs can add up quickly without oversight. There are a few reasons why users may not be getting the most value out of their Snowflake investment.  

  1. Snowflake is a newer offering compared to traditional data warehouses that have matured over decades. It does not yet provide all the fine-grained tuning tools that your DBAs typically use. 
  2. Snowflake users are likely a broad mix of business and technical users with varying levels of database proficiency, often resulting in poorly written queries, sub-optimal schemas and inefficient data ingestion and consumption patterns. 
  3. Snowflakes’ ease of scaling up/out has created a shortcut for solving performance problems allowing you to bypass best practice database optimizations at the cost of additional compute costs. 

Data To Value

Waste isn't good for any business. Instead of spinning cycles on deteriorated SQL queries, the data cloud provider would rather have you focus those Snowflake credits towards projects like building data apps. These types of projects provide higher value to your business and make their solution stickier and lead to more sustainable increased consumption in the long-term.

Bluesky is purpose-built to holistically analyze Snowflake workloads and optimize them by proactively identifying potential issues like unoptimized queries, repeatedly failing queries, orphan tables, and so on. With Bluesky, you can eliminate data infrastructure inefficiencies - not only improving your Snowflake user experience, but freeing up engineering and financial resources that, in turn, can be funneled back into your business.