×
![screenshot]()
MongoToDB batch migrates MongoDB data to 10+ relational databases with speed and security. Process millions of rows locally, support incremental sync, cross-platform, CLI, and scheduled tasks for enterprise-level efficiency.
MongoDB to Redshift
MongoDB to AZURE SQL
Migrate multiple MongoDB collections to relational database tables in one click. Support recursive collection scanning and automatic table naming based on collection names.
Optimized algorithm processes millions of rows in minutes. Handle large MongoDB datasets without memory limits, even for 100GB+ databases.
Automatically create relational database tables based on MongoDB collection structure. Preserve data types and relationships with zero manual configuration.
All data processing happens locally—no data transmission to cloud. Protect sensitive enterprise data with 100% privacy guarantee and ISO compliance.
Works seamlessly on Windows (32/64bit), Mac OS, and Linux (Debian/Ubuntu/Red Hat). Consistent experience across all operating systems.
Automate migrations with CLI support. Integrate with scripts and batch processes for hands-free data migration workflows in DevOps pipelines.
Set up daily/weekly scheduled sync tasks. Automate routine data migration and synchronization between MongoDB and relational databases.
Enter MongoDB connection string or select local instance. Support authentication, SSL/TLS, and MongoDB Atlas connections.
Select target relational database, configure table mapping, and choose migration mode (full/incremental).
Click "Migrate" and monitor progress in real-time. Get fully populated relational database tables in minutes.
Every collection becomes its own table, every document a row, with the tables created from the documents - one run, mapping visible first.
Sub-documents and arrays have to become columns. Turn on complex data, then check the flattened shape in the columns map.
No direct access, or the change has to go through somebody else: save the migration as a .sql file instead of inserting rows.
Re-run the saved task on a schedule with update/upsert, so changed documents refresh their rows instead of being added again.
By target database: MongoDB to MySQL, MongoDB to SQL Server, MongoDB to Oracle. One collection only: collection to table. Other MongoDB tasks: DBToMongo, MongoToFile, MongoLoader - the full set is on the MongoDB tools page.
MongoToDB processes millions of rows in minutes. The exact speed depends on your hardware, dataset size, and migration mode. A 1GB MongoDB collection typically takes 7-10 minutes to migrate to MySQL.
Yes. MongoToDB automatically creates tables in the target relational database based on MongoDB collection structure. It maps BSON data types to compatible SQL types and preserves field names and relationships. You can also customize table schema in advanced settings.
Absolutely. MongoToDB works with both local and cloud-based MongoDB instances (Atlas) and cloud relational databases (Amazon RDS, Azure SQL, Google Cloud SQL). Simply enter the connection strings for both systems during setup.
Yes. MongoToDB handles nested documents by either flattening them into the main table (with dot notation for field names) or creating related child tables to preserve the hierarchical structure—whichever best fits your target database schema.
Yes. All purchases include free technical support via email.
Connect to MongoDB and to the target database, choose the collection (or a query) and let MongoToDB create the table and write the rows. Fields become columns and nested documents are flattened.
Yes. If the table does not exist it is created from the documents, with a type chosen for each field. If it already exists, the fields are mapped onto the existing columns.
A script is fine for a single collection. MongoToDB adds automatic table creation, a field mapping you can review first, update and upsert instead of insert-only, batch migration across collections, a command line and scheduled sync tasks.
"We migrated our 120GB MongoDB customer database to SQL Server using MongoToDB in just 6 hours—something that would have taken 2 days with custom scripts. The automatic table creation feature saved our team 40+ hours of manual schema design."
"As a DevOps engineer, I needed a reliable way to sync MongoDB analytics data to PostgreSQL for reporting. MongoToDB's CLI integration fits perfectly into our nightly sync pipeline, and incremental sync reduced processing time from 2 hours to 15 minutes."
"We evaluated 4 different migration tools before choosing MongoToDB for its cross-platform support and nested document handling. Our team uses a mix of Mac and Linux servers, and the consistent experience across OSes is invaluable. The support team resolved our Oracle migration issue in under an hour."
Ready to Migrate MongoDB to Relational DB Effortlessly?
Download MongoToDB Free Trial