How to Use JSONB in PostgreSQL for Product Attributes Storage

Samuel
Folasayo
How to Use JSONB in PostgreSQL
for Product Attributes Storage
Demonstrating Best Practices and CRUD Operations with JSONB
Joe Nyirenda

Open-source relational database management system.
Advanced data types and powerful querying capabilities.
Designed for scalability, reliability, and SQL compliance.
Introduction to PostgreSQL
What is PostgreSQL?

PostgreSQL Pros & Cons
Pros
ACID compliance.
Rich data types support
(e.g., JSON, arrays, etc.).
Extensible via plugins and
procedures.
Free and open-source.
Cons
Steeper learning curve for
advanced features.
Higher memory
consumption for large
datasets.

What is JSONB?
JSONB Overview
Binary representation of JSON
data in PostgreSQL.
Allows indexing, searching, and
manipulating JSON data more
efficiently.
Better than plain JSON in
performance due to binary
format.
Example JSONB Object
{
"name": "Smartphone",
"price": 299.99,
"category": "Electronics",
"tags": ["mobile", "touchscreen", "camera"],
"details": {
"manufacturer": "TechBrand",
"model": "XPro 2024",
"features": {
"screen_size": "6.5 inches",
"battery": "4000mAh",
"camera": "12MP",
"storage": "128GB"
},
"warranty": "2 years",
"release_date": "2024-10-15"
}
}

Differences Between JSON and JSONB
in PostgreSQL
Storage Format
JSON: Text format
JSONB: Binary format (more efficient)
Indexing
JSON: Limited indexing
JSONB: Supports full indexing (faster
searches)
Performance
JSON: Slower reads (needs re-parsing)
JSONB: Faster reads (pre-parsed)
Flexibility
JSON: Preserves formatting
JSONB: Ideal for querying &
transformations
Insertion Speed
JSON: Faster to insert
JSONB: Slightly slower (binary
conversion)
Data Size
JSON: Stores all formatting
JSONB: Strips extra whitespace (smaller
size)
Modification
JSON: Limited field updates
JSONB: Allows field-level updates

JSONB Pros & Cons
Pros
Efficient storage and
indexing of JSON data.
Supports rich querying
capabilities (e.g., key-value
lookups, path queries).
Ideal for semi-structured
data.
Cons
Slight overhead for
converting JSON to binary
format.
Can become slower with
deeply nested or large
JSON structures.

Perfect for storing flexible, schema-less data.
Excellent for use cases where attributes vary across records (e.g.,
product attributes).
Facilitates easy expansion and adjustment of data models without
schema migration.
Why Use JSONB in PostgreSQL?
Why Use JSONB?

Sample Usage Scenarios for JSONB
Storing Product Attributes
CREATE TABLE products (
id serial PRIMARY KEY,
name text,
attributes jsonb
);
INSERT INTO products (name, attributes)
VALUES ('Laptop', '{"brand": "Dell",
"processor": "Intel i7", "ram": "16GB"}');
VALUES ('Phone', '{"brand": "Samsung",
"battery": "4000mAh", "ram": "8GB"}');
Querying Specific JSONB Fields
SELECT name, attributes->>'brand' AS brand
FROM products
WHERE attributes @> '{"ram": "16GB"}';
Why JSONB: Attributes vary for each
product.
Why JSONB: Efficient filtering and querying
based on specific fields.

Sample Usage Scenarios for JSONB -
Cont.
Combining JSONB with Traditional
Fields
UPDATE products
SET attributes = jsonb_set(attributes,
'{ram}', '"32GB"')
WHERE name = 'Laptop';
Indexing for Faster Queries
CREATE INDEX idx_product_attributes ON
products USING gin(attributes);
Why JSONB: Allows partial updates without
rewriting the whole JSON object.
Why JSONB: Full-text indexing for fast
retrieval of deeply nested fields.
Updating a Field Inside JSONB
SELECT name, attributes
FROM products
WHERE attributes->>'processor' = 'Intel i7';
Why JSONB: Seamlessly combines structured (name) and unstructured
(attributes) data in queries.

Create a table to store products with JSONB attributes.
Use JSONB for flexible product attributes:
Setting Up the Database
Install PostgreSQL & Create a Database
Create a new database:
createdb your_database_name
CREATE TABLE products (
id serial PRIMARY KEY,
name text,
attributes jsonb
);

Granting Necessary Permissions in
PostgreSQL
Make sure you have admin or necessary privileges:
GRANT ALL PRIVILEGES ON DATABASE your_database TO your_user;

Full CRUD Operations with JSONB
Create: Insert JSONB data into a table.
VALUES ('Laptop', '{"brand": "Dell", "specs": {"ram": "16GB",
"storage": "512GB"}}'::jsonb);
Read: Retrieve JSONB attributes and filter on keys.
SELECT name, attributes->'brand'
FROM products
WHERE attributes->>'ram' = '16GB';

Delete: Remove records, ensuring JSONB constraints are
respected.
Full CRUD Operations with JSONB - CONT.
Update: Modify specific fields in JSONB objects.
UPDATE products
SET attributes = jsonb_set(attributes, '{specs,storage}',
'"1TB"')
WHERE name = 'Laptop';
DELETE FROM products
WHERE attributes @> '{"brand": "Dell"}';

Python and PostgreSQL Integration
Technologies
psycopg2to connect to
PostgreSQL from Python.
Flask for creating a
lightweight web application.
Step-by-Step
Connect to the database using
psycopg2.
Define API endpoints using
Flask.
Perform CRUD operations and
ensure JSONB fields are
handled properly.

Index JSONB fields on frequently queried keys.
Use GIN indexes for better performance on complex JSONB queries.
Avoid overuse of JSONB for data that fits a strict schema.
GIN Indexes in PostgreSQL for
JSONB
Best Practices:
How to Create GIN Indexes:
CREATE INDEX idx_products_attributes ON products USING GIN (attributes);

Leverage PostgreSQL’s rich indexing and querying options for better
performance.
Combine GIN indexes with filters to optimize performance on JSONB data queries.
Optimization Tips for JSONB in
PostgreSQL
Use jsonb_path_ops GIN indexes for faster key lookups.
Example:
CREATE INDEX idx_products_path_ops ON products USING GIN (attributes
jsonb_path_ops);
Avoid deeply nested JSON structures for performance.
SELECT * FROM products WHERE attributes @> '{"color": "red"}';

Using JSONB for all fields in a table (only for flexible attributes).
Storing large blobs of JSON in a single record without proper
indexing.
Querying deep-nested JSONB without indexing leads to
performance issues.
JSONB Anti-Patterns
What to Avoid:

Set up Flask and PostgreSQL.
Create the CRUD operations for products table.
Use psycopg2.extras.Json to handle JSONB data in SQL queries.
Handle API requests to create, read, update, and delete product attributes.
Integrating CRUD Operations in index.html
Code Walkthrough
Step-by-Step Explanation:

Conclusion
JSONB is highly useful for semi-structured data.
PostgreSQL is powerful and flexible, enabling complex
querying.
Always apply best practices for indexing, querying, and
optimizing JSONB data.

How to Use JSONB in PostgreSQL for Product Attributes Storage

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