Guests John Kutay of Striim and Jacob Matson, VP of Finance and Operations, discuss the recent pricing changes in dbt Cloud and its implications for data teams and the open source community. They explore how companies should react and the impact on analytics engineering. The conversation covers the benefits of open source software, self-hosted alternatives to dbt, and the challenges of monetizing free tools.
Dbt Labs announced pricing changes for dbt cloud, including a new consumption-based model, to prioritize higher-value enterprise customers and raise revenue for company growth.
Users should focus on delivering tangible value and demonstrating the ROI of their analytics work, while also aligning key operational analytics projects with the organization's strategic goals to navigate pricing changes effectively.
Deep dives
Pricing changes on dbt cloud
Dbt Labs announced pricing changes for dbt cloud, including a new consumption-based model. The developer plan now allows for a maximum of 3,000 models built per month, while the team plan charges one cent per successful model built and includes a maximum of 15,000 models per month. This change aims to prioritize higher-value enterprise customers and raise revenue to support company growth.
Impact of pricing change
The pricing change has sparked mixed reactions in the community. Some users are reflecting on the value they receive from dbt cloud, considering the increased costs. However, this pricing pattern is not unique to dbt, as other open-source projects have also made monetization changes. The ease of deploying open-source tools in the cloud has contributed to this shift, leading to questions about how to balance sustainability and affordable access to quality tools.
Popular self-hosted alternatives
Users have discussed various self-hosted alternatives to dbt cloud. One option is to leverage GitHub actions and its integration with dbt for automated workflows. Other possibilities include deploying dbt on different cloud platforms such as GCP, AWS, or Azure. These alternatives provide flexibility and control while reducing reliance on a cloud-hosted service.
Navigating the pricing change and embracing value
Data teams should focus on delivering tangible value to mitigate the impact of pricing changes. Demonstrating the ROI of their analytics work is crucial in justifying costs. Additionally, teams should carefully consider their key operational analytics projects and ensure their alignment with the organization's strategic goals. By delivering value and prioritizing projects effectively, data teams can navigate pricing changes and maintain their position as essential contributors to business success.
The data industry was rocked by dbt Labs' announcement of changes to their pricing model. Striim's John Kutay brings on Jacob Matson who's fresh off his talk at MDS Fest 'Operational Analytics on Prod: using dbt & SQL Server for operational use cases' to break down the pricing changes.
John and Jacob discuss:
Overview of the dbt Cloud pricing changes
How it impacts data teams
What it means for the open source community at large
How data teams should react
Jacob Matson is VP of Finance and Operations at Simetric where he leads their operational data stack. Jacob is also the founder of MDS in a Box
What's New In Data is a data thought leadership series hosted by John Kutay who leads data and products at Striim. What's New In Data hosts industry practitioners to discuss latest trends, common patterns for real world data patterns, and analytics success stories.
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