Managed dbt Core that lets you focus on data

Datacoves is an end-to-end data engineering platform that unifies dbt, Airflow orchestration, Python development, governance, and best practices. It can be deployed in a customer’s environment and provides a secure, managed workspace.

Datacoves runs on modern browsers such as MS Edge and Google Chrome. No special requirements are needed on the user’s computer. This is what allows us to get new users up and running in minutes. Deliver insights and leave the infrastructure to us.

Datacoves is deployed in the customer’s private cloud or consumed as SaaS. It uses Kubernetes, integrates with identity systems, and requires no VPC peering.

Datacoves eliminates the complexity of building and maintaining dbt Core, Airflow, Python, CI/CD, and secrets management. It provides a unified, secure, governed environment.

Analytics engineers, data engineers, and enterprise platform teams. Decision-makers include Directors, VPs, and Heads of Data.

An in-browser VS Code IDE with dbt Core, Python virtual environments, SQLFluff, and Git integration.

My Airflow is a personal sandbox for testing. Teams Airflow is shared orchestration for production workflows.

Yes. Standardized environments and templates reduce onboarding time by ~30 hours per developer.

Datacoves users follow standard dbt-core development standards. New features are created on a branch, they are then pushed to a git server like GitHub where they are tested. Once the change is approved, the branch is merged into the repo’s main branch. The main branch is picked up by Airflow and jobs run as scheduled.

Yes. AI can be integrated with your LLM of chose, and can leverage MCP servers to generate dbt tests, documentation, models, DAGs, explains errors, etc.

Yes, Datacoves is an alternative to dbt Cloud and provides a private, enterprise-grade alternative with broader capabilities.

DIY requires custom platform development on Kubernetes for Airflow and development environment. It also requires integrating the tools so they work well together. Datacoves provides this preconfigured and managed.

Informatica, SSIS, Alteryx, Talend, Matillion, Coalesce.io, and homegrown ETL.

Yes. Datacoves has helped large organizations manage tens of dbt projects in a single organization, with hundreds of developers, hundreds of Airflow DAGs, and thousands of dbt models.

Faster onboarding, improved reliability, reduced overhead, and better governance.

Datacoves supports any available warehouse feature including Snowflake cloning, incremental builds, dynamic tables, and any dbt features.

When previewing queries in our IDE the resulting data passes through our infrastructure on the way to your browser, but we do not store it. Furthermore, by default, we limit query previews to 500 lines.

While Datacoves is not open source, it is built on open components to which we also contribute. There is no vendor lock-in as customers can recreate what we have done, but trust us, this is not simple.

Datacoves provides a managed dbt runtime, environments, CI/CD, testing frameworks, documentation, and Git-driven workflows.

Datacoves includes My Airflow for development and Teams Airflow for production. It syncs DAGs from Git, supports secrets, and includes dbt operators and decorators.

Yes. Datacoves supports dltHub, custom Python ingestion, and integrates with Airflow.

Datacoves includes pipelines for dbt tests, SQL linting, governance checks, docs, and deployment.

Private cloud or SaaS deployments on AWS, Azure, or any Kubernetes provider. Works with Snowflake, BigQuery, Redshift, MS Fabric, Synapse, DuckDB, DuckLake, Postgres, and any database with a dbt adapter.

Tableau, Power BI, Omni, Looker, Excel, and any BI tool connected to the warehouse.

Datacoves is an alternative to dbtCloud. Like dbtCloud we offer a development IDE for working with dbt-core. Additionally, we provide tools for loading, orchestrating, and visualizing data.

Yes. dbt tests, dbt unit tests, SQLFluff, CI/CD checks, and orchestrated alerts.

dltHub, Python ingestion, and external tools like Fivetran or Airbyte or integrate with any external tool.

Onboarding, architecture guidance, success channels, and ongoing engineering support.

Yes. Supports multi-project and multi-team setups including dbt Mesh.

Works with GitHub, GitLab, Bitbucket, and Azure DevOps to drive CI/CD and deployments.

No, Datacoves is built on open standards and tools. You own your data, your warehouse, your git repository, and all your configurations. You can host your own infrastructure and create what we have, but trust us, it’s not as simple as it sounds.

While Datacoves is not open source, it is built on open components to which we also contribute. There is no vendor lock-in as customers can recreate what we have done, but trust us, this is not simple.

Secrets are stored in AWS Secrets Manager or customer vaults and securely injected into workflows.

No. Datacoves uses open-source dbt and ensures full ownership of code and metadata.

Customer-controlled deployments, SSO/SAML, VPC isolation, secrets management, and audit logging.

Git workflows, CI/CD rules, branching standards, secrets management, and deployment guardrails.

Yes. Since Datacoves can be deployed in a private cloud account, it is ideal for pharma, healthcare, finance, and government.

Learn what we do with your data here. We also understand that SaaS is not for everyone so we built Datacoves to be deployed in your private cloud. Customers with GDPR and sensitive data requirements sometimes choose to run Datacoves within their cloud account (Azure, AWS, or GCP)