Managed Dbt + Airflow
Accelerate insights, not infrastructure
Skip the setup headaches. Datacoves gives you production-ready dbt and Airflow so your team can focus on building reliable data pipelines and driving business results.
VS Code in the browser
Develop instantly in a familiar VS Code environment, complete with your favorite extensions and full terminal access. Pre-configured with dbt-coves and Datacoves enhancements for accelerated dbt development.
SQL & Python support
Use any Python library you need to develop your models and DAGs. Flexibility at your fingertips.
My Airflow
Develop your DAGs in real-time with a single click. Immediate feedback, faster iterations.
SSO integration
Out-of-the-box Single Sign-On integration. No hassle, just secure access.
Managed upgrades for fast onboarding
Worry-free upgrades handled for you. Always develop on the latest and greatest without the headache. Onboard developers in minutes, not weeks.
Datacoves Co-pilot
AI assistance to streamline your development, saving you countless hours. Your intelligent partner in coding using your ChatGPT or secure Azure OpenAi.
See how Datacoves help transform data operations
J&J's data evolution: Innovating with Datacoves & dbt
“Datacoves really is a framework accelerator for us. They really are bringing automation tailored to our needs.”
Bart Vandendriessche, Manager Technology Services
Read StoryFrequently asked questions
Find answers to your questions below. Contact us if you couldn't find what you're looking for.
Contact UsCan Datacoves be deployed to my private cloud?
Yes. Datacoves deploys into your own cloud account on AWS, Azure or GCP, or any Kubernetes provider, so your data never leaves your control and no VPC peering is required. It integrates with what you already run: Jenkins, GitHub, GitLab, EntraID, Cortex, Claude Code and more. This is the usual choice for healthcare, pharma, finance and government teams, where getting a SaaS tool through a compliance review takes more time and effort.
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 Datacoves include AI capabilities?
Yes. AI coding tools run inside the browser VS Code environment: Claude Code, GitHub Copilot, Snowflake Cortex CLI, OpenAI Codex CLI and Gemini CLI, with MCP servers supported. You choose which LLM backs them, so the model stays your decision rather than the platform’s. Teams use them to generate dbt tests, documentation, models and DAGs, and to explain errors.
Does my team have to install and upgrade Datacoves in my private cloud?
No, Datacoves provides white-glove service: our team installs, upgrades, and troubleshoots within your firewall.
How does Datacoves handle dbt and Airflow version upgrades?
Upgrades are fully managed by the Datacoves team, your engineers only need to coordinate to schedule them. Your team is in control when versions of dbt are rolled out to specific environments. You also have the ability to move ahead of the Datacoves shipped dbt version by using our custom docker image process. Every upgrade can be tested and validated before it reaches your production environment.
How does Datacoves support CI/CD for analytics engineering teams?
Datacoves integrates with GitHub, GitLab, Bitbucket, and Azure DevOps, Jenkins and can work with other git or CI/CD providers. When a developer pushes a branch, CI/CD pipelines run automated tests before the merge. Once code merges to main, Airflow picks it up and executes jobs on schedule. Standard dbt workflow, production-ready from day one.
How is Datacoves different from building a data platform yourself?
DIY gives you flexibility but costs you time, consistency, and institutional knowledge. Teams that go that route spend months wiring together Airflow, dbt, Python environments, secrets management and CI/CD, then more months maintaining it as versions change. Datacoves delivers all of that preconfigured and managed.
How quickly can we get up and running with Datacoves?
Most teams are in a production-ready environment within days. Datacoves ships a fully preconfigured Turnkey Developer Environment including VS Code in the browser, dbt, Airflow, and SSO so no lengthy infrastructure setup is required. Developers can be onboarded in minutes. A private deployment can be done in weeks.
What does "white-glove service" mean in practice?
The Datacoves team handles installation, upgrades, and troubleshooting directly within your environment. For private cloud deployments, your team doesn’t manage Kubernetes, Docker images, or Airflow infrastructure. Datacoves engineers work inside your firewall so your data team stays focused on delivering insights. When feasible, Datacoves engineers are also able to communicate via existing tools like Slack or MS Teams for faster collaboration.
What is the difference between Datacoves and dbt Cloud?
dbt Cloud, now the dbt Platform, covers dbt development and scheduling and runs on dbt Labs’ infrastructure. Datacoves bundles Managed dbt, Managed Airflow, VS Code in the browser and governance guardrails into one subscription, and deploys into your own AWS, Azure or GCP account as well as multi-tenant SaaS.
Why do enterprises trust Datacoves for managing data?
“Datacoves enabled us to reduce time to market by delivering a secure pre-configured environment for dozens of Analytics Engineers and to implement best-in-class DataOps processes on a dbt and Snowflake foundation”
“Without Datacoves I would have needed a whole team to get all of these services put together and integrated”
“Datacoves solves the infrastructure problem. Datacoves packages together all the tools needed to support data teams of all sizes.”
“The stability, Kubernetes-backed scalability, and overall reliability of the Airflow environment have been the cornerstone of achieving our data system goals.”
“We have a background in Data Architecture, but building a way of managing dbt and Airflow together would have been a project in itself.”
End-to-end data analytics with Managed dbt and Airflow
Don’t let platform limitations or maintenance overhead hold you back.
