DASH ENTERPRISE

Databricks and Dash Integration

The founders of Databricks created Apache Spark, as well as other open-source data science and machine learning projects, making them valued Plotly partners. The Databricks platform offers a notebook interface, similar to Jupyter Notebooks, to leverage Apache Spark. Dash applications using Databricks can be easily developed and deployed to Dash Enterprise.

Databricks and Dash Integration

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Medium

Medium: Building Plotly Dash Apps on a Lakehouse with Databricks SQL

For building Plotly Dash apps on Databricks, the integration process is identical to any data warehouse. Use the databricks-sql python connector (DBSQL) to create a jdbc/odbc connection to a DBSQL endpoint, or use an ORM such as SQLAlchemy.

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Dash Apps Built with Dash Enterprise

Dash provides a friendly Python interface for creating flexible, interactive, and customizable apps that connect directly to your analytics code.

Dash-Databricks

Dash-Databricks

  • Databricks-dash is a closed-source, custom library that can be installed and imported on any Databricks notebook through Dash Enterprise.
Plotly

Dash Apps with Databricks

  • Seamlessly build Dash Apps on a Lakehouse with Databricks SQL. Use the databricks-sql python connector (DBSQL) to create a jdbc/odbc connection to a DBSQL endpoint, or use an ORM such as SQLAlchemy.
Dash-Databricks

Dash-Databricks

  • Databricks-dash is a closed-source, custom library that can be installed and imported on any Databricks notebook through Dash Enterprise.
Plotly

Dash Apps with Databricks

  • Seamlessly build Dash Apps on a Lakehouse with Databricks SQL. Use the databricks-sql python connector (DBSQL) to create a jdbc/odbc connection to a DBSQL endpoint, or use an ORM such as SQLAlchemy.

Architecture

Dask enables your production-grade Dash application to load and process very large datasets or models using distributed computing with familiar Python data science tools.

Architecture

Build. Deploy. Scale.

Dash Enterprise

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