Storing JSON in database vs. having a new column for each key

Storing JSON in Database vs. Having a New Column for Each Key: Which Is Better?

📝 As a developer, you may come across a common problem of deciding how to store user-related data in a database. One option is using JSON format to store all the data in a single column, while the other option is having a separate column for each key. Which approach is better, considering performance and design aspects? Let's dive into this dilemma and find some easy solutions!

The JSON Format Approach

🔑 In the JSON format approach, you would have two columns in your table - uid (as the primary key) and meta, which stores all the user data in JSON format. Here's an example:

uid | meta
--------------------------------------------------
1   | {"name": ["foo"], "emailid": ["foo@bar.com","bar@foo.com"]}
--------------------------------------------------
2   | {"name": ["sann"], "emailid": ["sann@bar.com","sann@foo.com"]}
--------------------------------------------------

✨ One advantage of this approach is the flexibility it offers. You can add as many fields as you need without having to modify the table structure. This can be useful when dealing with varying data requirements.

💡 However, the question remains: How can we query this data effectively? For instance, how can we fetch all the users whose name is similar to "foo"?

🔍 Querying JSON Data

🤔 Performing queries on JSON data is possible, but it requires specific techniques depending on the database system you are using. Let's focus on MySQL, as mentioned in the question.

➡️ To query the JSON data in MySQL, you can use the JSON_EXTRACT() function along with the LIKE operator. Here's an example:

SELECT *
FROM your_table
WHERE JSON_EXTRACT(meta, '$.name[0]') LIKE '%foo%';

📝 In the above query, we used JSON_EXTRACT() to extract the value of the "name" key from the meta column. The [0] implies that "name" is an array and we want to match the first element. Then, we used the LIKE operator to search for matches containing "foo" in the extracted value.

🔽 The Column-per-Field Model

🔑 In the column-per-field model, you would have separate columns for each user data field, similar to the traditional relational database structure. For example, your table might have columns like uid, name, and emailid.

🔀 So, which model is better in terms of performance and design? Well, it depends on your specific use case. If you have a large number of fields, the JSON format can offer more flexibility, allowing for easy addition of new fields. On the other hand, if you primarily perform queries on specific columns, the column-per-field model may be more efficient.

🔄 Combining Both Models

🌟 Since you mentioned that the number of searchable fields is limited, combining both models can be a good approach. You can use the column-per-field model for the data you frequently query and perform searches on, while using the JSON format for less frequently queried data. This way, you can strike a balance between flexibility and performance in your database design.

💪 Now that you have learned about the pros and cons of each approach and explored querying techniques, it's time for you to decide which model suits your specific needs. Remember, there is no one-size-fits-all solution, and careful consideration of your requirements is key!

💌 We hope this guide has helped you in your decision-making process. Let us know your thoughts and experiences in the comments below. Happy coding! 👩‍💻👨‍💻