Leverage the power and convenience of SQL for real-time analytics and reporting.
Seamless SQL Access to MongoDB Without Performance Trade-Offs
MongoDB is a powerful NoSQL database, but integrating it with SQL-based analytics, Business Intelligence tools, and data pipelines can be challenging. The Simba MongoDB ODBC and JDBC Drivers eliminate this friction by enabling direct SQL access while preserving MongoDB’s native performance.
Run SQL Queries on MongoDB — No Manual Workarounds Needed
Query MongoDB using SQL without complex scripting or data extraction.
Translate SQL queries into MongoDB-native operations, making NoSQL data accessible.
Optimized Query Performance With Pushdown Processing
Run queries natively in MongoDB instead of moving large datasets.
Push filters, joins, and aggregations directly to MongoDB for faster performance.
Automatically Structure NoSQL Data for SQL-Based Tools
Dynamically map JSON documents into a structured, SQL-compatible format.
Work with nested and semi-structured data in BI and analytics tools without manual schema definitions.
With Simba’s optimized drivers, teams gain faster insights, seamless integration, and SQL-friendly access to NoSQL data—without workarounds.
Connect your analytic applications directly to your MongoDB data using our Simba MongoDB ODBC and JDBC drivers with SQL Connector. Enjoy fast insights with powerful queries on both single and distributed MongoDB setups.
Since MongoDB doesn’t require a fixed schema, our SQL Connector automatically builds schemas as you go—and you can refine them further with our new Schema Editor. Plus, our built-in Collaborative Query Execution ensures filters and aggregations run directly on MongoDB for truly high-performance data access.
MongoDB’s JSON-based structure makes it hard to use in SQL-based analytics and reporting tools. The Simba Adapter eliminates this friction. Simba translates SQL into native MongoDB queries, enabling seamless data access without requiring NoSQL expertise.
Extracting MongoDB data into external databases adds latency and storage costs, reducing its real-time potential. Simba allows direct, real-time querying within MongoDB, keeping data where it belongs while maintaining performance.
SQL-based tools struggle with MongoDB’s flexible schema, leading to slow queries and inefficient processing. Simba pushes down queries, ensuring that filters, joins, and aggregations run natively in MongoDB for faster performance.
The Simba MongoDB Driver translates SQL into MongoDB-native queries, making NoSQL data fully accessible in SQL-based tools. Simba enables SQL-friendly access without manual exports, data reshaping, or custom scripting, saving time and effort.
Simba executes filters, aggregations, and joins directly in MongoDB, reducing data movement and improving query speeds. By optimizing queries natively, Simba lowers processing overhead, keeping MongoDB fast while ensuring efficient data access.
MongoDB’s flexible schema is automatically mapped into structured SQL tables, simplifying access to nested JSON data. Simba eliminates the need for manual schema definitions, making NoSQL data instantly usable in BI, analytics, and integration tools.
MongoDB stores diverse data types across industries. The Simba MongoDB Driver enables SQL-based access to customer data, logs, transactions, and more for analytics.
Customer Profiles
User Activity
Product Catalogs
Inventory Data
Orders & Transactions
Billing & Payments
Event Logs
IoT Sensor Data
Marketing Analytics
A/B Test Results
Operational Metrics
Support Tickets
Session Data
Machine Data
Content Metadata
SQL Access to MongoDB Data via ODBC and JDBC – Connect to MongoDB using SQL queries from analytics applications like Power BI, Tableau, Excel, QlikView, and more through both ODBC and JDBC interfaces.
ODBC 3.8 and JDBC 4.2 Compliant Connectors – Provides 32-bit and 64-bit ODBC 3.8 and JDBC 4.2 compliant connectivity for Windows, macOS, and Linux platforms.
Automatic Schema Mapping – Dynamically maps NoSQL MongoDB collections into relational tables, enabling seamless SQL-based querying.
Optimized Query Pushdown for Performance – Executes SQL queries natively in MongoDB, reducing data movement and improving response times for analytics and reporting
Aggregation Pipeline Support – Leverages MongoDB’s native aggregation framework, enabling efficient filtering, grouping, and analytics at scale.
Advanced Security & Compliance – Supports OAuth, Kerberos, LDAP, and SSL/TLS encryption, ensuring secure enterprise data access.
Batch Fetching & Pagination Support – Optimized batch retrieval and pagination mechanisms for handling large MongoDB datasets without overwhelming system memory.
Cross-Platform Compatibility – Compatible with multiple platforms, including Windows, Linux, and macOS for flexible deployment.
Supports MongoDB 6.x and 7.x – Fully compatible with modern MongoDB versions, ensuring long-term reliability.
32- and 64-Bit Application Support – Works seamlessly with both 32-bit and 64-bit applications.
ODBC and JDBC Compliance – Adheres to the ODBC 3.8 and JDBC 4.2 specifications for standardized database connectivity.
ANSI SQL Support – Enables SQL-based interactions with NoSQL data, making MongoDB accessible for BI, analytics, and reporting.
Unicode & Multi-Language Support – Handles international character sets, ensuring compatibility with global datasets.
Flexible Licensing Options – Offers departmental, enterprise, and worldwide licensing to fit various organizational needs.
FIPS Compliance & Enterprise Support – Meets strict security and compliance standards, ensuring trusted data access for regulated industries.
