Overview

Databricks is a unified data analytics platform built on Apache Spark, offering a collaborative environment for data engineering, data science, and machine learning:

  • Unified platform: Combines data engineering, data science, and analytics in one place
  • Delta Lake: ACID transactions and scalable metadata handling on data lakes
  • Collaborative notebooks: Share code, visualizations, and insights across teams
  • Multi-cloud support: Available on AWS, Azure, and Google Cloud
  • SQL Analytics: Run SQL queries on your data lakehouse with SQL Warehouses

Databricks is ideal for building data pipelines, training ML models, running SQL analytics, and creating real-time data applications.

Connecting

To connect to Databricks in DBCode, you’ll need:

  1. Open the DBCode Extension: Launch Visual Studio Code and open the DBCode extension.
  2. Add a New Connection: Click on the “Add Connection” icon.
  3. Complete connection form: Select Databricks as the database type and enter:
    • Host (e.g., adb-1234567890123456.7.azuredatabricks.net)
    • HTTP Path (from your SQL Warehouse or cluster settings)
    • Personal Access Token or use OAuth authentication
    • Catalog (optional, defaults to your workspace default)
  4. Connect: Click save to connect to your Databricks workspace.
  5. Start Managing Your Data: Explore catalogs, schemas, tables, and run queries.

For detailed instructions on connecting to Databricks, refer to the Connect article.

Authentication Methods

DBCode supports two authentication methods for Databricks:

Personal Access Token

Generate a personal access token in your Databricks workspace settings and use it as the password in your connection configuration.

OAuth (U2M)

Use browser-based OAuth authentication for enhanced security. When connecting, DBCode will open your browser to authenticate with your Databricks workspace.

Databricks Features in DBCode

DBCode enhances your Databricks development experience with:

  • Unity Catalog browsing: Navigate through catalogs, schemas, tables, and views
  • SQL editing: Write and execute SQL queries with syntax highlighting and autocomplete
  • Data preview: Quickly view sample data from tables
  • Session variables: Use connection pinning to maintain session state across queries
  • Function support: Browse and use user-defined functions

By using Databricks with DBCode, you can efficiently develop SQL queries, explore your data lakehouse, and manage your Unity Catalog objects directly within Visual Studio Code.

For more information about Databricks, check out Databricks.