DoiT Launches SELECT for Databricks to Automate Cost Optimization

SELECT brings its proven data platform optimization engine to Databricks, replacing manual cost management for engineering and data teams

SANTA CLARA, Calif., June 9, 2026 /PRNewswire/ -- DoiT today announced the extension of SELECT, its automated cost optimization product for data teams, to Databricks. SELECT now gives engineering and data teams full cost visibility and automated savings across their Databricks environments. The launch marks a major milestone in SELECT's mission to provide the best optimization solution for modern data platforms, extending capabilities proven across more than $250 million in Snowflake spend to one of the fastest-growing data platforms in enterprise technology.

The Databricks Cost Challenge

As organizations scale their data science, machine learning and ETL workloads on Databricks, cost management has become one of the most pressing operational challenges in enterprise engineering. Databricks' pricing model combines Databricks Units, which vary by workload type, instance size, edition tier and cloud provider, with underlying cloud infrastructure charges for compute, storage and networking. And as Databricks has become a primary home for AI model training and inference, model serving costs are growing rapidly, with even less native visibility and fewer controls than traditional workloads.

What makes this uniquely difficult is that every Databricks workload drives a parallel layer of cloud infrastructure spend that Databricks provisions under the hood, along with associated networking and cloud storage costs. These are billed directly by the cloud provider and not reflected in Databricks' own reporting, rendering true total cost of ownership impossible without dedicated tooling. Optimizing across these layers simultaneously, while preventing idle clusters, right-sizing compute resources and attributing costs by team or product, is a sustained commitment that most FinOps and engineering teams are not resourced to maintain manually.

"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."

How SELECT for Databricks Works

SELECT for Databricks integrates directly with Databricks, requiring only a read-only service principal and approximately 20 minutes of setup. The platform immediately begins ingesting billing metadata, aligning it against historical data to surface granular cost attribution across workspaces, teams, users, jobs and clusters. Key capabilities include:

• Automated Savings on All Workloads: Adjusts cluster configurations to reduce costs on all workloads by up to 30% with no ongoing engineering effort.
• Granular Cost Visibility: Track total DBU consumption and cloud infrastructure costs by workspace, environment, workload type (All-Purpose Compute, Job Clusters, SQL Warehouses, Model Serving), user, job and cluster.
• Fully Loaded Cost Attribution: Understand the true cost of each workload by combining Databricks DBU charges with the underlying cloud provider infrastructure costs, providing cost-per-job, cost-per-query and cost-per-user unit economics.
• Anomaly Detection and Alerting: Machine learning-powered anomaly detection automatically identifies unexpected cost spikes and notifies teams in real time, enabling fast triage and accountability across engineering organizations.
• Optimization Insights: Actionable recommendations surface cluster utilization inefficiencies, idle compute, auto-termination gaps, outdated runtimes and the costly inefficiencies that AI-generated code frequently introduces.
• Decentralized Cost Management: Flexibly assign Databricks costs to different teams and departments, equipping each with the tools to self-manage and govern their own spend.

A Foundation Built on Proven Expertise

SELECT's Databricks platform is built on the same automation engine the company has refined through production deployments across hundreds of Snowflake customers and more than $250 million in Snowflake spend. The platform runs on AWS, Azure and Google Cloud, and connects to Databricks via Unity Catalog-enabled system tables — the approach Databricks itself recommends for comprehensive cost monitoring and analysis.

"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. "Our team was able to focus on other valuable business initiatives instead of worrying about optimizing costs and building out our own monitoring."

Databricks is the second data platform supported by SELECT, joining Snowflake. Support for Google BigQuery is in early preview, completing SELECT's coverage of the three dominant platforms in the modern data stack. SELECT is available as a standalone product or as part of Cloud Intelligence™, DoiT's unified FinOps and CloudOps platform.

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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SOURCE DoiT