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Databricks vs Domino: What are the differences?
Developers describe Databricks as "A unified analytics platform, powered by Apache Spark". Databricks Unified Analytics Platform, from the original creators of Apache Spark™, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications. On the other hand, Domino is detailed as "A PaaS for data science - easily run R, Python or Matlab code in the cloud with automatic version control for data, code, and results". Use our cloud-hosted infrastructure to securely run your code on powerful hardware with a single command — without any changes to your code. If you have your own infrastructure, our Enterprise offering provides powerful, easy-to-use cluster management functionality behind your firewall.
Databricks belongs to "General Analytics" category of the tech stack, while Domino can be primarily classified under "Platform as a Service".
Some of the features offered by Databricks are:
- Built on Apache Spark and optimized for performance
- Reliable and Performant Data Lakes
- Interactive Data Science and Collaboration
On the other hand, Domino provides the following key features:
- Domino Cloud supports the most powerful data analysis languages — Python, R, MATLAB, and Julia
- Modern and powerful cluster management
- Use a single-core machine during development
Pros of Databricks
- Best Performances on large datasets1
- True lakehouse architecture1
- Scalability1
- Databricks doesn't get access to your data1
- Usage Based Billing1
- Security1
- Data stays in your cloud account1
- Multicloud1