How to Query MongoDB with "like"?

Querying data in MongoDB often requires pattern-matching operations similar to SQL's "LIKE" operator. While MongoDB doesn't have a direct "LIKE" operator, it offers the $regex operator and regular expressions for achieving similar functionality.

In this article, We will learn about How to Query MongoDB with "like" with the help of $regex and regular expression in detail along with the implementations and so on.

How to Query MongoDB with "like"?

To query MongoDB with a "like" operator equivalent, we can use the $regex operator along with regular expressions. However, MongoDB offers several methods to query MongoDB with "like" are defined below:

1. Using $regex Expressions
   
2. Using the Regular Operator

Syntax:

db.collection.find({ "field": { $regex: /pattern/i } });

• collection: The name of the MongoDB collection we want to query.
  
• "field": The field within the documents we want to query.
  
• /pattern/: The regular expression pattern we want to match.
  
• i: An optional flag that makes the pattern case-insensitive.

Let's set up an Environment:

To understand How to query MongoDB with "like" we need a collection and some documents on which we will perform various operations and queries. Here we will consider a collection called users which contains information like name, email, username, bio, and city of the Employees in various documents.

> db.users.insertMany([
   {
     "name": "John Doe",
     "email": "[email protected]",
     "username": "johndoe",
     "bio": "Software Engineer with a passion for coding",
     "city": "New York"
     },
    {
    "name": "Alice Smith",
    "email": "[email protected]",
    "username": "alicesmith",
    "bio": "Web Developer interested in UX design",
    "city": "San Francisco"
    },
    {
    "name": "francis",
    "email": "[email protected]",
    "username": "francis",
    "bio": "data scientist",
    "city": "Madagascar"
    }
    ]);

Output:

1. Using the $regex Operator

In MongoDB, the $regex operator is a powerful tool for performing pattern matching operations within queries. It allows for flexible searching based on regular expressions, enabling refined search capabilities similar to SQL's "LIKE" operator.

Example 1

Let's Retrieve documents from the "users" collection where the "name" field contains the case-insensitive string "john".

// Querying the documents where name contains with John
db.users.find({ "name": { $regex: /john/i } });

Output:

Explanation: In the above output, we quered all the documents where name contains with "john".

Example 2

Let's Find all documents in the "users" collection where the "username" field contains the case-insensitive string "alice"

// Querying the documents where username contains alice
db.users.find({ "username": { $regex: /alice/i } });

Output:

Explanation: In the above output, we quered all the documents where username contains "alice".

2. Using Regular Expressions

In MongoDB, Regular Expressions (regex) offer a powerful tool for querying and searching data based on specific patterns within fields. Regular expressions allow for flexible and dynamic searches, akin to SQL's "LIKE" operator.

Example 1:

Let's Retrieve documents from the "users" collection where the "bio" field contains the case-insensitive substring "data"

// Find documents where the bio contains "data" (case insensitive)
db.users.find({ bio: { $regex: /data/, $options: 'i' } })

Output:

Explanation: In the above output, we quered all the documents where username contains "alice".

Example 2

Let's Retrieve documents from the "users" collection where the "email" field contains the substring "john" using a multi-line matching pattern.

// Find documents where the email contains "john"
db.users.find({ email: { $regex: /john/, $options: 'm' } })

Output:

Explanation: In the above output, we quered all the documents where the email contains "john".

Conclusion

Overall, Querying MongoDB with "like" operators is a powerful feature provided by MongoDB's $regex operator and regular expressions. With the help of these features, you can perform flexible and dynamic searches within your MongoDB collections, enhancing your data querying capabilities.