Matillion’s drag-and-drop interface is a good alternative for UI based ETL workflows. However, it may be harder to customize, more expensive than others, and has a higher switching cost due to its proprietary nature.
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Matillion uses traditional UI based ETL, but Datacoves empowers all users
Matillion’s low-code, drag-and-drop interface follows a traditional UI based ELT pattern. However, it can be difficult for those not familiar with complex ETL tools. It can handle data ingestion and transformations, but is typically only available to IT data engineers.
Datacoves is the alternative that gives anyone with SQL knowledge the full power of dbt. Coupled with its seamless Airflow integration and fully configurable VS Code IDE, Datacoves offers the flexibility to handle more complex workflows with precision and scalability.
If you’re looking for a low-code platform that prioritizes ease of use over customization, Matillion might suit your needs. But if you need a developer-first platform that maximizes control and adaptability, Datacoves is the better fit without increasing vendor lock-in.
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Datacoves does not just offer a platform, but helps teams adopt new ways of working. Datacoves is helping us build better data products by providing tooling and processes for groups of data engineers to work together efficiently.
Denny Verbeeck
Sr Manager, Data Architect
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Why choose Datacoves?
End-to-end ELT
Datacoves provides a fully integrated ELT stack where teams can integrate existing tools or use the ones provided in the platform. Its tight integration with dbt and Airflow allows teams to manage everything in one environment without worrying about platform maintenance, tool upgrades, or managing multiple SaaS contracts
Matillion promotes a GUI approach to the EL process with built-in tools and a drag-and-drop interface. However, this approach limits the team's ability to customize and optimize SQL. Over time teams may choose to use their own code in SQL or dbt components, but this can become harder to manage as pipeline complexity grows. Matillion does offer pipeline orchestration, but it lacks the community and ecosystem of more established tools like Airflow.
Flexibility for the organization
Datacoves is built for the most challenging enterprise environments. Its flexibility enables teams to customize and extend their workflows with any VS Code Extension and Python Library. This level of flexibility is essential for organizations that need to adjust and optimize their data processes as they grow.
Matillion’s low-code approach is accessible to trained ETL developers coming from similar tools, but can be limiting for teams needing to customize their workflows. While it may appear simpler to use at first glance, it may not offer the level of flexibility as organizations needs evolve.
Scalability as you grow
Datacoves is designed to scale with the growing complexity of data operations. Its Kubernetes based managed Airflow solution enables Datacoves to efficiently handle large and complex workflows. Additionally, Datacoves Mesh enhances scalability by enabling large projects to be split into multiple smaller projects,
Matillion handles scalability well by pushing data operations down to the warehouse. However, organizations dealing with larger-scale operations might encounter limitations in Matillion’s native orchestration capabilities.
DataOps compatibility
Datacoves is fully compatible with modern DataOps practices with no black-box processes. Out of the box blueprints are provided to accelerate process maturity including best practices for CI/CD , dbt project architecture, blue-green deployments, data security and more. Datacoves helps reduce technical debt by establishing a mature process from the start.
Matillion’s GUI-based ETL can act like a "black box," limiting visibility into the underlying processes and making it difficult to do code reviews and ensure consistent standards. This can make debugging more difficult, as it’s harder to trace issues or pinpoint errors compared to a more transparent, code-based tool.
Vendor lock in
Datacoves minimizes vendor lock-in by leveraging open-source tools like dbt Core, Airflow, and incorporating best-in-class open source libraries that enhance developer productivity. Additionally, Datacoves is adaptable. When new open-source tools become available, they can extend parts of the stack so you stay aligned with evolving technology needs.
Matillion’s proprietary platform may appear to be user-friendly and effective, but it can lead to vendor lock-in, especially for teams relying on its built-in orchestration tools. While this isn’t an issue for all organizations, teams prioritizing long-term flexibility may need to consider how easily they can transition away from proprietary solutions. The higher per-user licensing and training requirements will limit the reach to all parts of the organization leading to siloed disconnected tools.
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.
Tobias Temmink
Data Management Lead
The Janssen Pharmaceutical Companies of Johnson & Johnson
Enabling modern DataOps
Datacoves does not just offer a platform, but helps teams adopt new ways of working. Datacoves is helping us build better data products by providing tooling and processes for groups of data engineers to work together efficiently.
Denny Verbeeck
Sr Manager, Data Architect
R&D Life Sciences