Supabase doesn't natively support dynamic schemas like a NoSQL database such as MongoDB. But hey, you can still create the illusion of a dynamic schema by using JSON and JSONB data types in PostgreSQL, which is what Supabase is built on. Just a heads-up, this method might have some limitations compared to a truly schema-less database.

In PostgreSQL, you have two types for handling JSON data: JSON and JSONB. JSONB stores data in a decomposed binary format. It's a bit slower to input because of conversion overhead, but it's way faster to process since it doesn't need to be reparsed.

To create a table with a JSONB column, run this SQL command in the Supabase SQL editor:

CREATE TABLE profiles (
    id serial PRIMARY KEY,
    data jsonb
);

Now, let's insert some JSON data into your new column.

INSERT INTO profiles (data) VALUES (
  '{"name": "John Doe", "email": "[email protected]", "age": 30}'
);

This will store JSON data in your table. But remember, if you're using this approach, schema validation won't be available. It's a good idea to perform data validation in your application before inserting the data into your database.

Just like any other PostgreSQL data type, you can query your JSONB column. The arrow operator (->) is used to query a specific property from your JSON data.

SELECT data->'name' as name 
FROM profiles
WHERE data->>'age' = '30';

This query will return the name of all profiles where the age is 30.

If performance becomes an issue when you have a large amount of JSON data in your PostgreSQL database, you can add an index to your JSONB column to improve query performance.

CREATE INDEX idxgin ON profiles USING gin (data jsonb_path_ops);

In this SQL statement, jsonb_path_ops is an operator class provided by PostgreSQL that helps us efficiently search within our JSONB data.

Note: When using this approach, make sure your "schema-less" data doesn't get too complex. This method is more suited to support flexibility in your data schema, not to fully replace the usage of schema-less databases.