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JDBC

MongoDB JDBC Driver

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

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

JDBC architecture

MongoDB JDBC Connectivity Features

  • Unmatched performance for reading large datasets
  • Compatible with MongoDB 2.6 and above
  • Enables SQL-92 capabilities on MongoDB NoSQL data.
  • Flexible NoSQL flattening - automatic schema generation, flexible querying etc.
  • Connect to live MongoDB data, for real-time data access with the MongoDB JDBC Driver
  • Full support for data aggregation and complex JOINs in SQL queries
  • Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the MongoDB Connector.

Target Service, API

The MongoDB JDBC driver models MongoDB instances as relational databases and supports MongoDB versions 2.6 through 7.0. We support not only MonogoDB hosted version, and DBaaS versions such as Atlas, CosmosDB with MongoDB API, and Amazon DocumentDEB Cluster. The driver leverages the MongoDB API, including the MongoDB aggregation framework, to enable bidirectional SQL access to MongoDB data.

Schema, Data Model

MongoDB is a schemaless, document database that provides high performance, availability, and scalability. The driver models the schemaless MongoDB objects into relational tables and translates SQL queries into MongoDB queries to get the requested data. The Automatic Schema Discovery scheme automatically finds the data types in a MongoDB object by scanning a configured number of rows of the object. You can use RowScanDepth, FlattenArrays, and FlattenObjects to control the relational representation of the collections in MongoDB. You can also write Free-Form Queries not tied to the schema.

Key Objects

User defined objects are exposed as relational tables.

Operations

You can use SELECT, INSERT, UPDATE, DELETE, CREATE TABLE, DROP TABLE, CACHE and many other SQL statements.

Authentication

The driver supports Authenticdation Schemes;, MONGODB-CR, SCRAM-SHA-1, SCRAM-SHA-256, PLAIN (LDAP), GSSAPI, and X509.

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JDBC access to MongoDB

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


See what you can do with MongoDB JDBC Driver

ETL, Data Warehouse
Data integration & ETL

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

Connect to MongoDB—empower every team

Management & Data Consumer
IT Department
ISVs & cloud service vendors

AI-assisted development with CData CLI

Build MongoDB integrations faster with AI that understands your schema

Schema-aware AI

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

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 MongoDB JDBC driver questions

Learn more about MongoDB JDBC drivers for data and analytics integration

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