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JDBC

Databricks JDBC Driver

Easily connect live Databricks data with Java-based BI, ETL, reporting, AI/ML & custom apps.

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The Databricks JDBC Driver enables users to connect with live Databricks , directly from any applications that support JDBC connectivity. Rapidly create and deploy powerful Java applications that integrate with Databricks data including Cluster, Jobs, Workspace, and more!

JDBC architecture

Databricks JDBC Connectivity Features

  • SQL access to Databricks lakehouses
  • Connect to live Databricks data, for real-time data access with the Databricks ADO.NET Provider
  • Full support for data aggregation and complex JOINs in SQL queries
  • Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
  • Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Databricks Connector.

Target Service, API

The driver supports all versions of Databricks from Runtime Versions 9.1 - 13.X including both Pro and Classic Databricks SQL versions. Compatible with Databricks clusters hosted on any cloud platform (AWS, Azure, GCP).

Schema, Data Model

Models Databricks data as relational tables with dynamic metadata discovery. The driver automatically detects table definitions data types and relationships. Supports Databricks Delta tables and provides access to workspace objects.

Key Objects

Databricks Clusters, Jobs, Workspace files, Notebooks, Delta tables, Views, and Databases. Provides access to both managed and external tables in the Databricks metastore.

Operations

Full CRUD operations with ANSI SQL-92 support. Pushes down filters, aggregations, and other SQL operations directly to Databricks for optimal performance. Supports complex JOINs and handles unsupported operations client-side. Enables batch operations and efficient data processing through Spark SQL integration.

Authentication

Supports Personal Access Token authentication, OAuth 2.0 (M2M and U2M), OAuth token pass-through, Azure Service Principal, and Azure AD authentication. Also supports OAuth 2.0 browser-based authentication for local applications.

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JDBC access to Databricks

Full-featured and consistent SQL access to any supported data source through JDBC


See what you can do with Databricks JDBC Driver

ETL, Data Warehouse
Data integration & ETL

Integrate Databricks into your systems and data warehouses through popular Java-based ETL/EAI tools. Supports both self-hosted environments and cloud service deployment.

BI, Reporting, Virtualization
BI, reporting & data virtualization

Connect to Databricks from any JDBC-compatible BI, reporting, and data virtualization platform. Provides seamless integration using SQL as the standard query interface across all tools.

Custom Java Applications
Custom Java applications

Use the Databricks JDBC Driver to rapidly deliver Java-based applications that connect with Databricks. Universal SQL-based interactivity simplifies integration and speeds time to market.

Connect to Databricks—empower every team

Management & Data Consumer
IT Department
ISVs & cloud service vendors

AI-assisted development with CData CLI

Build Databricks integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Databricks schema. No more guessing table names or column types—AI sees the same metadata in your JDBC Drivers.

Your AI knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Databricks.

More accurate, more token-efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
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FAQs

Frequently asked Databricks JDBC driver questions

Learn more about Databricks JDBC drivers for data and analytics integration

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