SELECT by DoiT Launches Early Access Program for Automated BigQuery Cost Optimization
In the realm of cloud data management, businesses are continually seeking ways to maximize their investment and optimize their spending. Recently, SELECT by DoiT, a company dedicated to data platform optimization, announced the launch of its Early Access Program for a new automated cost observability and optimization platform specifically designed for Google BigQuery. This innovative solution promises to assist engineering and data teams in controlling their cloud costs, a growing concern as companies increase their reliance on Google Cloud for analytics, machine learning, and AI workloads.
As organizations deepen their investments in Google Cloud, BigQuery emerges as a central piece of infrastructure, tasked with managing vast amounts of data and complex queries. However, it also introduces significant cost management challenges. BigQuery’s pricing model, which includes components like on-demand queries, slot-based capacity reservations, and storage billing, can become complicated, creating what SELECT by DoiT refers to as a 'Cost Visibility Gap.' Most teams struggle to optimize their spend effectively across these various pricing structures, often resulting in wasted expenditures due to failed or inefficient queries.
“Over the course of engaging with thousands of BigQuery customers, we have recognized the expertise needed to navigate and optimize for costs,” explained John Purcell, Chief Product Officer at DoiT. “Our automated platform is specifically designed to bridge that gap.”
The SELECT solution leverages a proven automation engine developed through handling over $250 million in Snowflake spend, alongside DoiT’s vast experience with BigQuery. This presents a strong foundation to build from. Ian Whitestone, GM and Co-Founder of SELECT by DoiT, emphasized that their solution is not just theoretical; it builds on years of practical engagement and expertise with nearly 2,000 BigQuery customers since its launch.
The SELECT BigQuery solution operates on an end-to-end basis, targeting cost optimization at three separate levels:
1. Storage Optimizer: This tool intelligently transforms tables from logical to physical storage billing, thus achieving cost savings without necessitating any modifications to queries or pipelines.
2. Reservations Manager: This feature continuously adjusts slot reservation capacities in accordance with actual workload demands, alleviating the need for manual analysis over time.
3. Query Router: It dynamically directs individual queries to the most economical billing pathway, optimizing between on-demand and reservation-based executions, while ensuring performance isn't compromised.
Furthermore, this tool integrates seamlessly with DoiT Cloud Intelligence™, which combines cost attribution, anomaly detection, and optimization management across various cloud infrastructures, including Kubernetes and Snowflake.
Currently, the Early Access Program is available for signup at select.dev/signup. This announcement coincides with the Google Cloud Next 2026 event in Las Vegas, where attendees can witness live demonstrations of the new product at SELECT by DoiT's booth. General availability is expected in the third quarter of 2026, following the introduction of similar solutions for Snowflake and Databricks.
SELECT by DoiT stands out as a premier platform optimization solution, specifically created to empower engineering and data teams to take control of their cloud spending. It delivers extensive insight into costs and performance across major platforms like Snowflake, Databricks, and now BigQuery. The company's automation technology has already proven effective across substantial customer spend, and this latest expansion into BigQuery enhances their reach within the modern data stack.
DoiT, the parent company, is a global leader in cloud intelligence, providing integrated solutions tailored to help businesses enhance the efficiency of their cloud investments. Their approach links spending directly to workload goals and identifies inefficiencies, enabling genuine optimization through automated actions. To learn more about their offerings, visit doit.com.
The Challenge of Cost Management
As organizations deepen their investments in Google Cloud, BigQuery emerges as a central piece of infrastructure, tasked with managing vast amounts of data and complex queries. However, it also introduces significant cost management challenges. BigQuery’s pricing model, which includes components like on-demand queries, slot-based capacity reservations, and storage billing, can become complicated, creating what SELECT by DoiT refers to as a 'Cost Visibility Gap.' Most teams struggle to optimize their spend effectively across these various pricing structures, often resulting in wasted expenditures due to failed or inefficient queries.
“Over the course of engaging with thousands of BigQuery customers, we have recognized the expertise needed to navigate and optimize for costs,” explained John Purcell, Chief Product Officer at DoiT. “Our automated platform is specifically designed to bridge that gap.”
Leveraging Experience for Solutions
The SELECT solution leverages a proven automation engine developed through handling over $250 million in Snowflake spend, alongside DoiT’s vast experience with BigQuery. This presents a strong foundation to build from. Ian Whitestone, GM and Co-Founder of SELECT by DoiT, emphasized that their solution is not just theoretical; it builds on years of practical engagement and expertise with nearly 2,000 BigQuery customers since its launch.
How the Automated Solution Works
The SELECT BigQuery solution operates on an end-to-end basis, targeting cost optimization at three separate levels:
1. Storage Optimizer: This tool intelligently transforms tables from logical to physical storage billing, thus achieving cost savings without necessitating any modifications to queries or pipelines.
2. Reservations Manager: This feature continuously adjusts slot reservation capacities in accordance with actual workload demands, alleviating the need for manual analysis over time.
3. Query Router: It dynamically directs individual queries to the most economical billing pathway, optimizing between on-demand and reservation-based executions, while ensuring performance isn't compromised.
Furthermore, this tool integrates seamlessly with DoiT Cloud Intelligence™, which combines cost attribution, anomaly detection, and optimization management across various cloud infrastructures, including Kubernetes and Snowflake.
Early Access Program
Currently, the Early Access Program is available for signup at select.dev/signup. This announcement coincides with the Google Cloud Next 2026 event in Las Vegas, where attendees can witness live demonstrations of the new product at SELECT by DoiT's booth. General availability is expected in the third quarter of 2026, following the introduction of similar solutions for Snowflake and Databricks.
About the Companies
SELECT by DoiT stands out as a premier platform optimization solution, specifically created to empower engineering and data teams to take control of their cloud spending. It delivers extensive insight into costs and performance across major platforms like Snowflake, Databricks, and now BigQuery. The company's automation technology has already proven effective across substantial customer spend, and this latest expansion into BigQuery enhances their reach within the modern data stack.
DoiT, the parent company, is a global leader in cloud intelligence, providing integrated solutions tailored to help businesses enhance the efficiency of their cloud investments. Their approach links spending directly to workload goals and identifies inefficiencies, enabling genuine optimization through automated actions. To learn more about their offerings, visit doit.com.
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