Convert SQL queries to MongoDB
SELECTfind()INSERTinsertOne()UPDATEupdateMany()DELETEdeleteMany()WHEREfilter objectORDER BYsort()LIMITlimit()LIKE$regexFree online SQL queries to MongoDB queries conversion tool from Mavis Digital. Support converting SELECT to find(), INSERT to insertOne(), UPDATE to updateMany(), DELETE to deleteMany(). Automatically parse WHERE conditions into MongoDB filter objects. Supports ORDER BY to sort(), LIMIT to limit(). Convert LIKE to $regex. Display SQL mapping table → MongoDB operators. There are 5+ SQL queries examples available to test. Useful for developers migrating from SQL database to MongoDB or learning MongoDB query syntax.
Converting SQL to MongoDB queries is useful in many situations. Migration: When migrating an application from SQL database (MySQL, PostgreSQL) to MongoDB, you need to convert existing queries. Learning: Developers familiar with SQL can learn MongoDB syntax by comparing it with equivalent SQL. Prototyping: Quickly convert SQL queries for testing on MongoDB. Documentation: Create documentation for the team transitioning to MongoDB. Code review: Verify MongoDB queries by comparing with SQL logic. This tool helps automate conversions, saving time and reducing errors.
Not yet. MongoDB uses $lookup aggregation for joins, which has a different structure than SQL JOIN. Convert JOIN needs to analyze schema and relationships, which is more complicated than simple queries. Recommend: Redesign data model for MongoDB (denormalization) instead of converting JOINs directly.
Not yet. GROUP BY in MongoDB uses aggregation pipeline with $group stage, a big difference from SQL. Aggregation queries need to be converted manually or use MongoDB Compass to build.
SQL UPDATE without LIMIT affects all matching rows. The MongoDB equivalent is updateMany(). If you only want to update 1 document, use updateOne() and make sure the filter is unique (like _id).
SQL LIKE with wildcards (%) converted to MongoDB $regex. For example: LIKE '%john%' → { $regex: '.*john.*' }. Note: Regex may be slower than LIKE on large collections if there is no text index.
Tool generates MongoDB syntax based on SQL input. Output needs to be tested on MongoDB shell or application to verify. Complex queries may require manual adjustment.
Tool parse standard SQL syntax, compatible with MySQL, PostgreSQL, SQL Server, SQLite. Database-specific syntax may not be recognized.
Not yet. Subqueries in MongoDB often use aggregation pipelines or need restructure queries. Convert subqueries require case-by-case analysis.
Output is MongoDB shell syntax. To use in code (Node.js, Python, etc.), the syntax needs to be adjusted a bit. For example: db.collection.find() → collection.find() in Mongoose.
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