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

database

data-modeling

database-design

performance-optimization

byAnton Shumikhin·Oct 30, 2024

Opt for JSON storage when you're dealing with dynamic, changing data, and sticking to your schema feels like fitting a square peg in a round hole. Use multiple columns when your data is as consistent as a metronome and you need the speed of Usain Bolt in a database. Here's the essence:

-- JSON, best mate for mood swings
CREATE TABLE users (
    id SERIAL,
    attributes JSONB   -- PostgreSQL's JSONB: Unpredictable schema's best buddy
);

-- Columns, when speed is your middle name
CREATE TABLE users (
    id SERIAL,
    name TEXT,
    birthdate DATE,
    email TEXT
);

In simple terms: JSON is your dear friend in chaos; columns are the rock in the rolling sea. Choose wisely based on the personality of your data and your need for performance.

When to swing: JSON vs. columns

Mood swinger? Or steady Freddy?

Your data can be a mood swinger or a steady Freddy. If it's like the weather in London - changing every five minutes - JSON gives you the flexibility to go with the flow, ideal for rapid prototyping and no migration headaches. But when your data consistency is akin to Bob Ross's painting style, then the columnar approach offers energy-efficient queries and optimized indexing.

JDBC: JSON's Driving Benefits Chart

JSON storage is your autonomous car, taking charge of semi-structured data with user-specific preferences, settings, or metadata in the driving seat. But even the smartest cars need efficient fuel; complex queries and searches can drain JSON's performance. Enter the columnar approach. It's your classic muscle car, known for its speed and performance, well-suited for data with an infrequent detour.

Blueprint and remodeling

Before deciding between a cottage or a castle, consider how your data's blueprint might change over time. While starting with a JSON field might feel like a jazz freestyle, the rhythm can become dissonant over time, creating technical debt. A columnar model, on the other hand, is the symphony playing in harmony, where even metadata is scored on a separate table, ensuring maintainable data just like Mozart's compositions.

When you want to have it all

Hybrid beasts

You might be tempted to tame a grizzly bear and ride a cheetah at the same time—similarly, you can combine JSON and columns. Keep main attributes in separate columns, and cuddle secondary attributes in a cozy JSON field. Balance is the key, as this hybrid might become a chimaera, making your system complex.

Tuning performance

Creating indexes on JSON fields sounds cool but might not be Sonic when it comes to speed. Before you make JSON your rave partner, ensure your groove patterns—or rather, query patterns—are what JSON can jive with.

Health check

Striding the JSON path means shifting data validation from the safe hands of your database to your potentially chaotic application layer. Also, if you're thinking of taking a vacation in the NoSQL world with MongoDB, make sure your travel needs—the application's data usage—justify the journey.

explain-codes / Database / Storing JSON in database vs. having a new column for each key

Linked

Most efficient conversion of ResultSet to JSON?



Index for finding an element in a JSON array



Best JSON-LD practices: using multiple <script> elements?



What is the easiest way to ignore a JPA field during persistence?



How to convert hashmap to JSON object in Java

