Integrated Orchestration
Smarter data orchestration, ingest, cleanse and activate
Get an enterprise class data orchestration optimized for dbt. With managed Airflow, and end-to-end observability, Datacoves streamlines deployments and frees your team to build, not maintain.
Secrets manager
Use our built-in Secrets manager or integrate with AWS Secrets Manager to securely store sensitive information, ensuring your data pipelines operate safely and comply with stringent compliance requirements and best practices.
SSO & user management
Simplify access with Single Sign-On and streamlined user management, enhancing security while reducing administrative overhead.
"My Airflow" per user
Provide dedicated Airflow environments for each user, streamlining development and testing.
Seamless data analytics with managed dbt and managed Airflow
Don’t let platform limitations or maintenance overhead hold you back.
See it in Action
Observability
Proactive monitoring and swift response to pipeline events with out of the box email, Slack, and Teams integrations. Use our Grafana, or integrate with your observability tool.
External API integration
Easily connect with external services and APIs, expanding the capabilities of your data workflows and facilitating seamless integrations.
Virtual environments & decorators for dbt
Simplified dbt development with pre-configured virtual environments and custom Airflow decorators. Run dbt commands seamlessly without managing dependencies or complex configurations. Focus on building and deploying your data models efficiently, not managing infrastructure.
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 UsDoes Datacoves support standard Airflow features?
Yes, Datacoves runs the same Airflow you can run yourself, managed so your team never has to handle the application layer.
What notification options exist for alerting on failures?
Email, Slack, and Teams out of the box, plus Grafana integration and notifications.
Do developers need to install Airflow locally to test DAGs?
No, My Airflow provides a browser-based personal Airflow environment per developer with a single click.
How is Datacoves' Airflow different from setting up Airflow ourselves?
Self-managed Airflow requires your team to provision infrastructure, manage Docker images, handle Kubernetes, configure secrets, and coordinate upgrades, all before you write a single DAG. Datacoves delivers a production-ready Airflow environment with managed upgrades, built-in secrets management, SSO, and per-user dev environments. The result: your data engineers spend their time building pipelines rather than operating Airflow.
Can we orchestrate tasks beyond dbt, for example triggering external APIs or ML pipelines?
Yes. Datacoves' Airflow supports the full Airflow operator library, including HTTP and Python operators, as well as custom decorators. Your DAGs can trigger external APIs, run Python scripts, kick off ML workflows, and integrate with tools such as Spark, dbt, and Airbyte within a single directed acyclic graph.
How does Datacoves handle failed pipeline runs and recovery?
Airflow's built-in retry logic handles transient failures automatically. Datacoves layers in proactive alerting via email, Slack, or Teams so your team is notified the moment something fails, not when a stakeholder reports a stale dashboard. For critical pipelines, SLAs can be configured to escalate if a run does not complete within a defined window.
What makes Datacoves different from Prefect or Dagster for dbt orchestration?
Prefect and Dagster are general-purpose orchestrators that can run dbt, but they require additional configuration, custom adapters, and separate infrastructure decisions. Datacoves is specifically built around the dbt development workflow, it ships custom dbt Airflow decorators, virtual environments pre-configured for dbt, and a development environment (VS Code + My Airflow) that mirrors production. Teams get an end-to-end platform rather than assembling one from parts.
What is "My Airflow" and why does it matter?
My Airflow gives each developer a personal, isolated Airflow instance accessible from the browser with a single click. Developers can test DAGs against real connections and variables without affecting the shared production environment. This removes one of the most common friction points in Airflow development: waiting for a DevOps team to provision a local or staging environment before you can test your logic.
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.”
Seamless data analytics with managed dbt and Airflow
Don’t let platform limitations or maintenance overhead hold you back.
Datacoves is an enterprise DataOps platform with managed dbt Core and Airflow for data transformation and orchestration, as well as VS Code in the browser for development
