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Built on open source

Databricks engineers are the original creators of some of the world’s most popular open source data technologies

Built on open data and AI projects trusted by millions of developers

Apache Spark™

Apache Spark is a unified engine for executing data engineering, data science and ML workloads.

What is Apache Spark?

Comparing Spark and Databricks


Delta Lake

Delta Lake lets you build a lakehouse architecture on top of storage systems such as AWS S3, ADLS, GCS and HDFS.

Learn more about Delta Lake


Tech Talks: Getting Started with Delta Lake


MLflow manages the ML lifecycle, including experimentation, reproducibility, deployment and a central model registry.

Managed MLflow on Databricks


Tech Talks: Managing the ML Lifecycle


Redash enables anyone to leverage SQL to explore, query, visualize, and share data from both big and small data sources.

Visit Redash on GitHub

Delta Sharing

Delta Sharing is the industry’s first open protocol for secure data sharing, making it simple to share data with other organizations.

Visit Delta Sharing

Databricks supports these additional popular open source technologies


Databricks supports TensorFlow, a library for deep learning and general computation on clusters

TensorFlow on Databricks


Facebook, the creator of PyTorch, and Databricks have collaborated on integrations

PyTorch on Databricks


Deep learning API written in Python, running on top of TensorFlow. Available in Databricks Runtime for ML

Keras on Databricks


An open source suite of tools for collaborative data science using R ​

R programming on big data


Widely used Python package for machine learning built on top of NumPy, SciPy and Matplotlib​​

Scikit-learn on Databricks


A distributed gradient boosting library that has bindings in languages such as Python, R and C++

XGBoost on Databricks


HashiCorp Terraform is a popular open source tool for creating safe and predictable cloud infrastructure across several cloud providers. Databricks Terraform provider allows customers to manage their entire Databricks workspaces along with the rest of their infrastructure using a flexible, powerful tool. Using Terraform also encourages customers to adopt best practices with infrastructure as code (IaC)

Terraform on Databricks

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