Databricks is primarily a cloud-based platform that major cloud providers like Azure and AWS manage. However, there’s a way to get some of its capabilities on-premises:

Databricks Lakehouse Platform: This is the closest to having Databricks on-premises. It allows you to deploy and manage your own Databricks environment within your infrastructure. This gives you more control over your data and infrastructure but requires you to handle the setup, maintenance, and updates yourself.

Connecting to On-Premises Data Sources: Whether using the cloud-based Databricks or the Lakehouse Platform, you can still connect to your on-premises data sources. Databricks supports various connectors to access data stored in databases, file systems, and other systems on your local network.

Here’s how you can connect to on-premises data sources:

1. Virtual Private Network (VPN): Establish a secure connection between your Databricks environment and your on-premises network, creating a private tunnel for data transfer.
2. Databricks Connect: This lets you connect your local development environment (e.g., Jupyter notebooks) to your Databricks cluster and access on-premises data.
3. JDBC/ODBC Drivers: Use standard database drivers to connect to on-premises databases directly from your Databricks notebooks or jobs.

Considerations:

• Security: Ensure you have robust security measures to protect your on-premises data when accessing it from Databricks.
• Network Latency: Be aware of potential latency when transferring data between your on-premises environment and Databricks.
• Maintenance: If you choose the Lakehouse Platform, you’ll be responsible for managing and updating your Databricks environment.