dbt Labs Comparables
Find the most relevant public market comparables for dbt Labs, including EV/Revenue and EV/EBITDA multiples to help you make informed investment decisions.
Company Overview
dbt Labs is a company that develops and provides dbt, an open-source command-line tool and a cloud-based platform that helps analysts and engineers transform data in their warehouse more effectively. It enables analytics engineers to transform data by writing SQL statements, turning them into tables and views. It focuses on the transformation (T) step in ELT (Extract, Load, Transform) processes. dbt Labs also fosters a large community around its open-source tool.
Business Model
SaaS (Software as a Service) offering a cloud-based platform (dbt Cloud) built upon an open-source command-line tool (dbt Core). The company also offers consulting services and support.
Target Customers
Data analysts, data engineers, and data teams in companies of various sizes, ranging from startups to large enterprises.
Specific Focus
Analytics Engineering, Data Transformation, ELT (Extract, Load, Transform)
Location
Philadelphia, Pennsylvania
CEO
Tristan Handy
Industry
Software & services
Sub Sector
Data Analytics and Management
3yr Revenue Growth
1,756%
Website
Public Market Comparables
Below are the key valuation metrics for companies similar to dbt Labs in the Software sector. These metrics can help you understand how the market values companies with similar business models and growth profiles.
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Unlock the Full dbt Labs Compset
As a leading player in the Software & services industry within the Software sector, dbt Labs operates in the specialized Data Analytics and Management sub-sector. Understanding how dbt Labs compares to its public market comps is essential for accurate valuation and strategic decision-making.
Our comprehensive analysis includes detailed comparables (compsets) featuring similar companies in the Data Analytics and Management space, with complete financial metrics, growth trajectories, and competitive positioning insights that go beyond the surface-level data shown above.
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