DoiT has announced the expansion of SELECT, its automated cost optimization platform for data teams, to Databricks environments. The launch extends SELECT’s optimization and cost visibility capabilities beyond Snowflake, enabling enterprises to monitor and reduce spending across Databricks workloads and the underlying cloud infrastructure that supports them.
The release reflects growing enterprise demand for more comprehensive cost management as organizations scale data science, AI, machine learning, and ETL operations across cloud-native data platforms.
Quick Intel
According to DoiT, Databricks cost optimization has become increasingly complex as enterprises expand AI, analytics, and machine learning operations.
The company stated that Databricks environments generate layered spending structures that combine Databricks Unit (DBU) charges with separate cloud infrastructure costs for compute, storage, and networking.
These infrastructure expenses are billed independently through cloud providers and are often not fully reflected in Databricks-native reporting systems, making total cost visibility difficult for engineering and FinOps teams.
As organizations scale AI model training and inference workloads, managing these combined costs has become a major operational priority.
“The scale of data-based workloads keeps growing, and so does the bill,” said Ian Whitestone, GM and co-founder of SELECT. “One of the biggest pain points for Databricks users is that their true cost lives within both the platform and the underlying cloud provider. SELECT for Databricks gives full visibility into both, and then takes continuous, automated action to reduce those costs.”
SELECT for Databricks integrates directly with Databricks environments using a read-only service principal and can be configured in approximately 20 minutes, according to the company.
Once connected, the platform ingests billing metadata and aligns it with historical usage data to provide detailed cost attribution across:
The system supports workload categories including:
DoiT stated that SELECT combines Databricks billing information with underlying cloud infrastructure expenses to provide fully loaded workload cost analysis.
The platform includes automation capabilities designed to reduce operational overhead for engineering and FinOps teams.
According to DoiT, SELECT can automatically optimize cluster configurations to lower workload costs by up to 30% without ongoing manual intervention.
Additional platform capabilities include:
The company also highlighted that the platform helps identify inefficiencies introduced by AI-generated code and rapidly scaling AI workloads.
SELECT is designed to operate across AWS, Microsoft Azure, and Google Cloud environments and connects to Databricks through Unity Catalog-enabled system tables.
The Databricks launch builds on SELECT’s existing deployments across Snowflake environments, where the company states the platform has already optimized more than $250 million in Snowflake spending.
“We got up and running with SELECT in about 20 minutes and we were able to drop our usage by 15% in just two days, which freed up the budget for other workloads,” said Marcus Wong, director of business intelligence at Clearco.
DoiT stated that Databricks is the second major data platform supported by SELECT, with Google BigQuery support currently in early preview.
The company aims to provide unified optimization capabilities across the three dominant enterprise data platforms as organizations continue modernizing cloud-based analytics and AI infrastructure.
SELECT is available both as a standalone platform and as part of Cloud Intelligence™, DoiT’s broader FinOps and CloudOps platform focused on cloud cost governance, infrastructure optimization, and operational efficiency.
As enterprise AI adoption accelerates, platforms capable of delivering automated cost visibility and optimization across increasingly complex cloud data ecosystems are becoming a central priority for engineering and finance teams alike.
About SELECT
SELECT is a leading platform optimization solution, purpose-built to help engineering and data teams control and reduce cloud data platform spend. The platform delivers deep visibility into cost and performance across Snowflake, Databricks and BigQuery, and takes continuous, automated actions to reduce cost without compromising performance. Visit select.dev to learn more.
About DoiT
DoiT keeps your cloud infrastructure always at its best. The Cloud Intelligence™ platform combines AI-driven FinOps automation with Forward Deployed Engineers who work alongside customer teams to ship real savings, not just recommendations. Across AWS, Google Cloud and Azure, DoiT manages more than $20 billion in cloud spend for 4,500 customers in 27 countries, with a 99.7% average customer satisfaction score. The platform covers Kubernetes, commitment management, data platform optimization and FinOps automation. To learn more, visit doit.com.
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