dbt Cloud is the easiest way to get started with dbt, but teams may hit limitations as they mature in their dbt use and workflows become more complex.
dbt Cloud is easy to get started but Datacoves offers ultimate flexibility.
dbt Cloud’s intuitive interface makes it easy for teams to get started with dbt, offering basic job scheduling and a managed development environment. However, as projects grow in complexity, its limited flexibility may restrict teams needing more control over their end-to-end data management.
For teams requiring greater customization, a self-hosted dbt Core environment provides the full power of dbt. However, managing such a setup can introduce significant overhead in terms of time, cost, and expertise. Datacoves delivers the best of both worlds with the control and customization of a self-hosted dbt Core setup, combined with the ease of a managed experience like dbt Cloud.
With a pre-configured VS Code environment, Datacoves gives technical users a familiar, customizable, and flexible workspace. Its also important to note, while dbt Cloud is good for Transformations, you will always need additional tools for orchestration as complexity grows. Datacoves has solved for this with its Managed Airflow solution, allowing teams to orchestrate not only Transformations but the full ELT pipeline in an integrated way.
If simplicity is your priority, dbt Cloud is a solid choice. But for teams seeking the flexibility of custom workflows, the convenience of managed services, and a platform designed to handle the entire ELT+ process, Datacoves is the clear winner.
Datacoves solves the infrastructure problem. Datacoves packages together all the tools needed to support data teams of all sizes.
Why choose Datacoves?
End-to-end ELT
Flexibility for the organization
Scalability as you grow
DataOps compatibility
Vendor lock in
Frequently asked questions
Find answers to your questions below. Contact us if you couldn't find what you're looking for.
Contact UsIs Datacoves a dbt Cloud alternative?
Yes. Datacoves is an alternative to dbt Cloud, now the dbt Platform. It runs Managed dbt and Managed Airflow in your own cloud, with VS Code in the browser, pre-built CI/CD pipelines, secrets management and governance guardrails. Teams pick it when a SaaS deployment doesn’t fit: private deployment in their own cloud, data residency rules, or a security review that rules hosted tooling out. See the dbt Cloud comparison.
Can a data platform run in our own region for data residency?
It depends on whether the platform deploys into your cloud account or the vendor’s. Datacoves Private Deployment runs inside your own AWS, Azure or GCP account, so the region is the one you already use and the data never leaves it. SaaS tools process data in the vendor’s region instead, which is the constraint teams under GDPR or sector residency rules meet first. See plans for what each deployment includes.
Can dbt Cloud run in my own AWS or Azure account?
No. The dbt platform is hosted by dbt Labs. Enterprise+ adds PrivateLink, IP restrictions, and Hybrid Projects for running dbt in your environment, but the platform itself stays in dbt Labs’ cloud. Datacoves deploys the whole platform inside your own cloud account.
Can we migrate our existing dbt Cloud or dbt Core project to Datacoves?
Yes. Datacoves connects to your existing Git repository, so your dbt models and Airflow DAGs move over without restructuring. Datacoves has helped teams migrate from both self-managed setups and dbt Cloud with minimal disruption.
Does dbt Cloud support Airflow?
No. dbt Cloud includes its own built-in scheduler for dbt jobs but does not provide or manage Airflow. Teams that need Airflow for end-to-end pipeline orchestration, including ingestion, transformation, and activation steps, must run and maintain it separately alongside dbt Cloud. This is one of the most common gaps enterprise teams hit as their pipelines grow.
How do I choose between dbt Cloud, dbt Core, and a managed platform?
Start with two questions. Does your data need to stay inside a private cloud, and does your team have the capacity to build and maintain platform infrastructure? If it does need to stay private and you don’t have that capacity, a Managed dbt platform is the right call. dbt Cloud, now the dbt Platform, is a strong fit for smaller, SQL-first teams that want fast setup and minimal DevOps. Running dbt Core (now dbt v1) yourself makes sense when you have platform engineering resources and customization requirements that no managed option can meet.
Is dbt Cloud the same as the dbt platform?
Yes. dbt Labs renamed dbt Cloud to the dbt platform. Most buyers still search for it as dbt Cloud.
Is there vendor lock-in?
No. Datacoves uses standard dbt, Airflow, and VS Code functionality. Your code is always yours. If you ever choose to move off Datacoves, you can take your code and run it on another platform.
When does dbt Cloud become expensive?
dbt Cloud’s Starter plan starts at $100 per developer per month, capped at five developers. Beyond that, teams move to Enterprise pricing. Semantic Layer usage and Copilot are metered separately. Teams with larger engineering organizations or heavy AI-assisted workflows often find the total cost significantly higher than the entry price suggests.
Why do teams move away from dbt Cloud?
Teams usually start on dbt Cloud for good reasons: it’s hosted, there’s no infrastructure to run, and they can be productive the same week. The reasons to move come later. The platform stays in dbt Labs’ cloud, which matters once data residency or a security review rules SaaS out. Its scheduler covers dbt jobs, so pipelines that reach ingestion and activation need an orchestrator alongside it, and cost meters successful model builds on top of seats, 15,000 a month on Starter and 100,000 on Enterprise. Teams at that point want the same hosted experience inside their own cloud, with Airflow and the full VS Code environment included.
What our clients have to say
Thought leadership on data engineering
Datacoves allowed us to switch to more modern technology stack but most of all adopt a different mindset and approach to building and maintaining data pipelines and working with data as an asset.
All-in-one data stack in the cloud
Datacoves solves the infrastructure problem. Datacoves packages together all the tools needed to support data teams of all sizes.
End-to-end data analytics with Managed dbt and Airflow
Don’t let platform limitations or maintenance overhead hold you back.
