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JDBC

Apache Spark JDBC Driver

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

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The Spark JDBC Driver enables users to connect with live Spark data, directly from any applications that support JDBC connectivity. Rapidly create and deploy powerful Java applications that integrate with Spark.

JDBC architecture

Spark JDBC Connectivity Features

  • Maps SQL to Spark SQL, enabling direct standard SQL-92 access to Apache Spark
  • Fully compatible with the DataBricks Enterprise Platform
  • Connect to live Apache Spark SQL data, for real-time data access with the Apache Spark SQL ODBC Driver
  • 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 Spark Connector.

Target Service, API

The driver connects to Apache Spark via Spark SQL. Big data processing.

Schema, Data Model

Models Spark tables and DataFrames. Supports various data sources.

Key Objects

Databases, Tables, and Views. Spark SQL catalog access.

Operations

Spark SQL queries. Read/write to various formats. No direct Spark job control.

Authentication

Varies by deployment. Kerberos for secure clusters.

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JDBC access to Apache Spark SQL

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


See what you can do with Spark JDBC Driver

ETL, Data Warehouse
Data integration & ETL

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

Connect to Spark—empower every team

Management & Data Consumer
IT Department
ISVs & cloud service vendors

AI-assisted development with CData CLI

Build Spark integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Spark 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 Spark.

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
Download CData CLI
FAQs

Frequently asked Spark JDBC driver questions

Learn more about Spark JDBC drivers for data and analytics integration

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