SQL to MongoDB query syntax

Why should SQL be converted to MongoDB query?

As the demand for scalability and flexibility in Internet applications increases, more and more projects are being developed from traditional relationship databases (e.g. MySQL), which are not available in the Internet. PostgreSQL) to document-type database MongoDB。 However, for developers who are used to structured query language (SQL), the JSON of MongoDB Style query syntax (MQL) has a certain learning curve.

The tool aims to address the following specific issues:

• Cost of moving to study: Help developers quickly understand the equivalent of the SQL concept in the MongoDB.
• Compositing: SQL GROUP BY and HAVING It's complicated in MongoDB. $group and $match Pipeline, manual writing is prone to error.
• Query optimization validation: The consistency of business logic is ensured through conversions that compare the search logic under different databases.

SQL versus MongoDB Core Concept

Advanced Conversion Techniques

1. WHERE Sub-Param conversion

Simple equals WHERE a = 1 Convert to { a: 1 } 。 But for range queries, MongoDB uses operator:

• > Correspond $gt
• >= Correspond $gte
• < Correspond $lt
• <= Correspond $lte
• != Correspond $ne

2. LIKE Fuzzy Query

SQL LIKE '%abc%' In MongoDB, regular expressions are usually used to achieve: { field: /abc/ } 。 This tool automatically generates the right to process prefixes, suffixes and contains matching.

3. Syndication and grouping (GRUP BY)

That's the most complex part. The syndication function for SQL is as follows: COUNT() , SUM() Needed in MongoDB $group Defined in the phase. For example:
SELECT user_id, SUM(price) FROM orders GROUP BY user_id
After conversion:
db.orders.aggregate([{ $group: { _id: "$user_id", total: { $sum: "$price" } } }])

Common issues (FAQ)