PostgreSQL is known for its powerful relational database features, but it also provides excellent support for storing and querying JSON data.

If you’re working with PostgreSQL, you’ll commonly encounter two JSON-related data types:

JSON
JSONB

At first, they may look almost identical. Both can store JSON documents, objects, arrays, and other valid JSON values.

However, JSON and JSONB store and process data differently, and choosing the right one can affect query performance, indexing, storage, and application behavior.

JSON stores the original JSON representation, while JSONB stores a decomposed binary representation that is generally better for querying and indexing.

In this guide, we’ll compare PostgreSQL JSON vs JSONB and explain when you should use each.

We’ll cover:

• What JSON is
• What JSONB is
• JSON vs JSONB
• Storage differences
• Query performance
• Indexing
• Duplicate keys
• Key ordering
• Whitespace
• JSON operators
• JSONB indexing
• When to use JSON
• When to use JSONB
• Common mistakes
• Practical examples
• Best practices

---

What Is JSON in PostgreSQL?

JSON is a PostgreSQL data type that stores valid JSON data.

For example:

CREATE TABLE users (
    id BIGSERIAL PRIMARY KEY,
    profile JSON
);

You can insert:

INSERT INTO users (profile)
VALUES (
    '{
        "name": "Oliver",
        "age": 28,
        "city": "London"
    }'
);

The JSON value represents structured data:

{
  "name": "Oliver",
  "age": 28,
  "city": "London"
}

PostgreSQL validates that the value is valid JSON.

---

What Is JSONB?

JSONB stands for JSON Binary.

It also stores valid JSON data, but PostgreSQL converts the input into an internal binary representation.

For example:

CREATE TABLE users (
    id BIGSERIAL PRIMARY KEY,
    profile JSONB
);

You can insert the same document:

INSERT INTO users (profile)
VALUES (
    '{
        "name": "Oliver",
        "age": 28,
        "city": "London"
    }'
);

The important difference is what happens internally after PostgreSQL receives the data.

---

JSON vs JSONB: Simple Explanation

The easiest way to understand the difference is:

JSON
 ↓
Stores JSON representation

JSONB
 ↓
Parses and stores data in binary form

Think of it this way:

JSON
→ Preserve the input representation

JSONB
→ Optimize the representation for processing

This difference affects how PostgreSQL handles whitespace, key order, duplicate keys, indexing, and querying.

---

JSON vs JSONB Comparison

Feature	JSON	JSONB
Stores JSON	Yes	Yes
Validates JSON	Yes	Yes
Preserves whitespace	Yes	No
Preserves key order	Yes	No
Preserves duplicate keys	Yes	No
Querying	Good	Excellent
Indexing	Limited	Excellent
Storage format	Text representation	Binary representation
Input processing	Less transformation	More processing during input
Typical Use	Preserve original JSON	Query and manipulate JSON

For most application use cases where JSON data needs to be queried, JSONB is usually the preferred choice.

---

1. Storage Format

The biggest difference is how the data is stored.

JSON

PostgreSQL stores the JSON representation of the value.

For example:

{
    "name": "Oliver",
    "age": 28
}

Whitespace and formatting are preserved.

---

JSONB

PostgreSQL parses the JSON and stores it in a decomposed binary representation.

The formatting isn’t preserved.

For example:

{
    "name": "Oliver",
    "age": 28
}

and:

{"age":28,"name":"Oliver"}

represent the same JSON object for JSONB purposes.

---

2. Whitespace

JSON preserves whitespace.

For example:

{
    "name": "Oliver"
}

The formatting is retained.

JSONB does not preserve that whitespace.

So these:

{
    "name": "Oliver"
}

and:

{"name":"Oliver"}

produce the same logical JSONB value.

If preserving the exact original formatting matters, JSON may be more appropriate.

---

3. Key Order

JSON preserves the order of object keys as supplied.

For example:

{
    "name": "Oliver",
    "age": 28,
    "city": "London"
}

JSON keeps that representation.

JSONB does not guarantee preservation of object key order.

This means you should not rely on JSONB to return object keys in the same order they were inserted.

---

4. Duplicate Keys

This is an important difference.

Consider:

{
    "name": "Oliver",
    "name": "Ethan"
}

A JSON object technically contains duplicate keys here.

With PostgreSQL’s JSON type, the original text representation is preserved.

When JSON is processed into JSONB, duplicate object keys are not preserved as separate entries. The later value takes precedence.

So JSONB effectively becomes:

{
    "name": "Ethan"
}

This is another reason to use JSON when preserving the exact original JSON representation is important.

---

5. Query Performance

One of the biggest advantages of JSONB is querying.

Suppose you have:

CREATE TABLE products (
    id BIGSERIAL PRIMARY KEY,
    metadata JSONB
);

And the data is:

{
    "brand": "NovaTech",
    "color": "black",
    "price": 799
}

You can query:

SELECT *
FROM products
WHERE metadata->>'brand' = 'NovaTech';

PostgreSQL can efficiently process JSONB data because it has already been converted into its internal representation.

---

JSONB Query Example

Suppose we have:

{
    "brand": "NovaTech",
    "color": "black",
    "features": [
        "wireless",
        "compact"
    ]
}

You can extract the brand:

SELECT metadata->>'brand'
FROM products;

Result:

NovaTech

You can also extract nested values using JSON operators.

---

6. JSON Operators

PostgreSQL provides operators for working with JSON and JSONB.

->

Returns a JSON value.

SELECT metadata->'brand'
FROM products;

Result:

"NovaTech"

->>

Returns a text value.

SELECT metadata->>'brand'
FROM products;

Result:

NovaTech

This distinction is very important.

---

7. Nested JSON

Suppose you store:

{
    "manufacturer": {
        "name": "NovaTech",
        "country": "UK"
    }
}

You can access nested values:

SELECT metadata->'manufacturer'->>'name'
FROM products;

Result:

NovaTech

You can continue navigating through nested JSON structures.

---

8. JSONB Containment Operator

One of the most useful JSONB operators is:

@>

It checks whether one JSONB value contains another.

For example:

SELECT *
FROM products
WHERE metadata @> '{"brand": "NovaTech"}';

This asks:

Does the metadata JSONB value contain "brand": "NovaTech"?

This type of query can benefit from a GIN index.

---

9. JSONB GIN Index

Suppose you frequently run:

SELECT *
FROM products
WHERE metadata @> '{"brand": "NovaTech"}';

You can create:

CREATE INDEX idx_products_metadata
ON products
USING GIN(metadata);

Now PostgreSQL has an index specifically designed for this kind of JSONB search.

Conceptually:

JSONB Query
     ↓
GIN Index
     ↓
Matching Documents

This is one of the biggest practical advantages of JSONB.

---

10. JSONB and Indexing

JSONB supports powerful indexing options.

A common choice is:

CREATE INDEX idx_products_metadata
ON products
USING GIN(metadata);

GIN indexes can be useful for:

• JSONB containment
• Key existence queries
• Arrays
• Full-text search

However, indexes consume storage and add write overhead.

Don’t automatically add a GIN index to every JSONB column.

Create indexes based on actual query patterns.

---

11. Key Existence Queries

PostgreSQL provides the ? operator for checking whether a JSONB object contains a key.

For example:

SELECT *
FROM products
WHERE metadata ? 'brand';

This checks whether the brand key exists.

You can also check multiple keys with operators such as:

?
?|
?&

For example:

SELECT *
FROM products
WHERE metadata ?| ARRAY['brand', 'manufacturer'];

This checks whether at least one of the specified keys exists.

---

12. JSONB Arrays

JSONB can store arrays.

For example:

{
    "name": "Oliver",
    "skills": [
        "Java",
        "PostgreSQL",
        "Spring Boot"
    ]
}

You can query the array:

SELECT *
FROM users
WHERE profile @> '{"skills": ["Java"]}';

With a suitable GIN index, this type of query can be efficient.

---

13. JSONB Modification

PostgreSQL provides operators and functions for modifying JSONB values.

For example:

UPDATE users
SET profile = jsonb_set(
    profile,
    '{city}',
    '"London"'
)
WHERE id = 1;

This updates the city value inside the JSONB document.

---

14. Adding Data to JSONB

You can use the concatenation operator:

||

For example:

UPDATE users
SET profile =
    profile || '{"verified": true}'
WHERE id = 1;

The JSONB object is updated with:

{
    "verified": true
}

JSONB provides many functions and operators for manipulating structured data.

---

15. Removing JSONB Fields

You can remove a key using:

-

For example:

UPDATE users
SET profile = profile - 'age'
WHERE id = 1;

This removes the age key from the JSONB object.

---

16. JSON Functions

PostgreSQL provides many functions for working with JSON and JSONB.

Some useful functions include:

jsonb_set()
jsonb_build_object()
jsonb_array_elements()
jsonb_object_keys()
jsonb_each()

For example:

SELECT jsonb_object_keys(profile)
FROM users;

This can return the keys contained in a JSONB object.

---

17. JSON vs JSONB Performance

When comparing performance, there are two important areas:

Write / Input
Read / Query

JSON

JSON can have less transformation overhead during input because PostgreSQL stores the JSON representation.

JSONB

JSONB does more work when data is inserted because PostgreSQL parses and converts the JSON into its binary representation.

However, JSONB is generally much more useful for querying and indexing.

So:

JSON
→ Potentially simpler input representation

JSONB
→ Better querying and indexing

The exact performance difference depends on the workload.

---

18. Storage Size

There is no universal rule that JSONB is always smaller than JSON.

JSON preserves the original textual representation, including whitespace.

JSONB removes insignificant whitespace and stores data in an internal representation.

Depending on the document structure, JSONB can use more or less storage than the original JSON text.

Therefore, don’t choose between JSON and JSONB solely based on storage size.

Measure your actual data if storage is important.

---

19. When Should You Use JSON?

JSON can be a good choice when you need to preserve the original JSON representation.

For example:

External API Payloads
Raw Event Data
Original JSON Documents
Data Where Formatting Matters

Suppose your application receives:

{
    "name": "Oliver",
    "age": 28
}

and you need to retain the exact representation for auditing or later processing.

JSON may be appropriate.

---

20. When Should You Use JSONB?

JSONB is usually the better choice when you need to:

• Query JSON frequently
• Index JSON data
• Search inside documents
• Modify JSON values
• Use JSONB operators
• Work with flexible application metadata

For example:

Product Metadata
User Preferences
Application Settings
Flexible Attributes
Event Metadata

JSONB is especially useful when the JSON data is part of your application’s queryable data model.

---

21. JSONB for Product Metadata

Imagine an e-commerce application where products have different attributes.

A laptop might have:

{
    "ram": "16GB",
    "storage": "512GB",
    "processor": "Core i7"
}

A phone might have:

{
    "screenSize": "6.7",
    "camera": "50MP",
    "battery": "5000mAh"
}

Instead of adding a separate database column for every possible attribute, JSONB can store flexible metadata.

CREATE TABLE products (
    id BIGSERIAL PRIMARY KEY,
    name TEXT NOT NULL,
    metadata JSONB
);

This is a practical use case for JSONB.

---

22. JSONB Does Not Replace Relational Design

One common mistake is putting everything into one JSONB column.

For example:

users
│
└── data JSONB
      ├── name
      ├── email
      ├── orders
      ├── payments
      └── addresses

This may seem convenient, but it can make relationships, constraints, and querying more difficult.

If something is a core entity in your application, relational tables may be more appropriate.

For example:

users
orders
payments
addresses

JSONB is often best used for flexible attributes, not as a replacement for the entire relational model.

---

23. PostgreSQL: Relational + JSONB

One of PostgreSQL’s biggest strengths is that you don’t necessarily have to choose between relational data and JSON.

You can combine them.

For example:

CREATE TABLE products (
    id BIGSERIAL PRIMARY KEY,
    name TEXT NOT NULL,
    price NUMERIC(10, 2) NOT NULL,
    metadata JSONB
);

Now you have:

Structured Columns
        +
Flexible JSONB Metadata

This hybrid approach is extremely useful for modern applications.

---

24. JSON vs JSONB Example

Let’s compare two tables.

JSON

CREATE TABLE api_logs (
    id BIGSERIAL PRIMARY KEY,
    payload JSON
);

JSONB

CREATE TABLE events (
    id BIGSERIAL PRIMARY KEY,
    payload JSONB
);

Use JSON when preserving the original representation matters.

Use JSONB when the application needs to search, filter, index, or manipulate the JSON data frequently.

---

25. JSONB and Spring Boot

If you’re using Java and Spring Boot, PostgreSQL JSONB can be useful for flexible fields.

A typical architecture might look like:

Spring Boot
    ↓
JPA / Hibernate
    ↓
JDBC
    ↓
PostgreSQL
    ↓
JSONB

For example, a product might contain:

id
name
price
metadata

where:

metadata → JSONB

The exact Java mapping approach depends on your Hibernate/Spring Data setup and the version of the libraries you’re using.

---

26. JSON vs JSONB: Which One Should You Choose?

Use this simple rule:

Need to preserve exact JSON representation?
        ↓
       JSON

If not:

Need to query/index/manipulate JSON?
        ↓
      JSONB

For most application development scenarios:

JSONB is the default choice.

But that doesn’t mean JSON is useless.

JSON is valuable when preserving the original JSON representation is important.

---

Common Mistakes

1. Choosing JSONB Automatically

JSONB is usually the better application choice, but not every workload requires it.

Understand why you’re storing JSON.

---

2. Storing Everything in JSONB

Don’t use JSONB simply because it is flexible.

Core entities and relationships are often better represented with relational tables.

---

3. Adding a GIN Index Without a Need

GIN indexes can be powerful, but they add storage and write overhead.

Create them when your query patterns justify them.

---

4. Ignoring Data Validation

Flexible JSON structures can become inconsistent.

For example:

{
    "price": 799
}

and:

{
    "price": "799"
}

may create application-level inconsistencies.

Define and enforce a consistent structure where appropriate.

---

5. Creating Deeply Nested Documents

Very deeply nested JSON can become difficult to query and maintain.

Keep JSON structures reasonably organized.

---

Best Practices

Use JSONB for Queryable JSON

If your application frequently searches or filters JSON data, JSONB is usually the better choice.

Use JSON When Representation Matters

Choose JSON when preserving whitespace, key order, or duplicate-key representation is important.

Index JSONB Selectively

Use GIN or other appropriate indexes for real query patterns.

Keep Core Relationships Relational

Don’t replace foreign keys and normalized tables with JSONB unnecessarily.

Define a Consistent Structure

Flexible schema doesn’t mean unstructured data should become chaotic.

Monitor Query Performance

Use:

EXPLAIN ANALYZE

to understand how PostgreSQL executes JSON and JSONB queries.

---

JSON vs JSONB Cheat Sheet

Requirement	Recommended
Preserve original JSON text	JSON
Preserve whitespace	JSON
Preserve key order	JSON
Preserve duplicate keys	JSON
Frequent querying	JSONB
Frequent filtering	JSONB
Indexing	JSONB
JSONB containment queries	JSONB
Flexible application metadata	JSONB
General PostgreSQL application use	Usually JSONB

---

Final Thoughts

PostgreSQL’s support for both JSON and JSONB gives developers flexibility when working with semi-structured data.

The core difference is simple:

JSON
↓
Preserves the original JSON representation

JSONB
↓
Stores a decomposed binary representation
and is optimized for querying and indexing

For most modern application workloads, JSONB is the better default because it provides powerful querying, indexing, and manipulation capabilities.

However, JSON still has an important role when the exact original representation of the JSON needs to be preserved.

The best PostgreSQL design often combines both relational and JSONB features:

PostgreSQL
│
├── Relational Tables
│      ↓
│   Core Application Data
│
└── JSONB
       ↓
   Flexible Metadata

Use relational columns for data that needs strong structure and relationships, and use JSONB when you need flexible, queryable attributes.