When designing a PostgreSQL database, one of the first decisions you’ll make is how to generate unique IDs for your records.

Two popular choices are:

UUID

and:

Auto-Increment ID

For example, an auto-incrementing ID might look like:

1
2
3
4
5

while a UUID might look like:

550e8400-e29b-41d4-a716-446655440000

Both approaches are reliable and widely used. The right choice depends on your application’s architecture, security requirements, database size, and how IDs are generated.

In this guide, we’ll compare PostgreSQL UUID vs auto-increment IDs, including their differences, advantages, disadvantages, performance, indexing, security, distributed systems, and practical recommendations.

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What Is an Auto-Increment ID?

An auto-increment ID is a numeric identifier that PostgreSQL generates automatically when a new row is inserted.

A modern PostgreSQL table can use an identity column:

CREATE TABLE users (
    id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    name TEXT NOT NULL,
    email TEXT NOT NULL
);

When you insert:

INSERT INTO users (name, email)
VALUES ('Oliver', 'oliver@example.com');

PostgreSQL generates the ID automatically.

The resulting data might look like:

id    name
---   -------
1     Oliver
2     Sophia
3     Ethan
4     Emma

---

What Is a UUID?

UUID stands for:

Universally Unique Identifier

It is a 128-bit identifier designed to provide a very large space of possible values.

Example:

550e8400-e29b-41d4-a716-446655440000

PostgreSQL has a native UUID data type:

CREATE TABLE users (
    id UUID PRIMARY KEY,
    name TEXT NOT NULL,
    email TEXT NOT NULL
);

You can generate UUID values using PostgreSQL-supported UUID generation functions.

For example:

INSERT INTO users (id, name, email)
VALUES (
    gen_random_uuid(),
    'Oliver',
    'oliver@example.com'
);

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UUID vs Auto-Increment: Quick Comparison

Feature	UUID	Auto-Increment ID
Data type	UUID	INTEGER / BIGINT
Size	16 bytes	4 or 8 bytes
Human readability	Lower	Higher
Sequential	Usually not	Yes
Distributed generation	Excellent	Requires coordination
Index size	Larger	Smaller
Insert locality	Depends on UUID strategy	Excellent
Guessability	Low	High
URL exposure	Less predictable	Easy to enumerate
Simple setup	Easy	Very easy
Best for	Distributed/public IDs	Traditional relational systems

---

How Auto-Increment IDs Work

PostgreSQL identity columns generate values from an associated sequence mechanism.

For example:

CREATE TABLE products (
    id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    name TEXT NOT NULL
);

Insert several products:

INSERT INTO products (name)
VALUES ('Laptop');

INSERT INTO products (name)
VALUES ('Keyboard');

INSERT INTO products (name)
VALUES ('Mouse');

You might get:

id    name
---   --------
1     Laptop
2     Keyboard
3     Mouse

The values are generally increasing, although you should not treat them as a perfect guarantee of gapless numbering.

---

What Does Auto-Increment Actually Guarantee?

A common misconception is:

Auto-increment IDs are always consecutive.

That’s not guaranteed.

For example:

1
2
3
5
6

ID 4 may be missing because a transaction consumed a sequence value and then rolled back, or because rows were deleted.

Therefore, don’t use database IDs as:

Invoice number
Order number
Human-facing sequence

unless you have deliberately designed a separate numbering system with the required business semantics.

---

How UUIDs Work

UUIDs provide a huge identifier space.

For example:

550e8400-e29b-41d4-a716-446655440000

Another UUID might be:

2f8b6c1e-5a5f-4c2e-91b0-8a4d7d8a2c10

The probability of an accidental collision is extremely small when UUIDs are generated correctly.

This makes UUIDs particularly useful when identifiers need to be generated independently across multiple systems.

---

UUID Generation in PostgreSQL

Modern PostgreSQL installations can use:

SELECT gen_random_uuid();

For example:

CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    name TEXT NOT NULL,
    email TEXT NOT NULL
);

Now PostgreSQL can generate a UUID automatically:

INSERT INTO users (name, email)
VALUES ('Oliver', 'oliver@example.com');

The database generates the ID.

---

Auto-Increment Performance

Numeric IDs have a major advantage:

They are compact.

A PostgreSQL BIGINT requires 8 bytes, while a UUID requires 16 bytes.

That difference matters when you have:

Millions of rows
Large indexes
Many foreign keys
Multiple related tables

For example:

users.id
    ↓
orders.user_id
    ↓
payments.user_id

If all these columns use UUIDs, the identifiers and associated indexes are larger.

With BIGINT, they are smaller.

---

UUID Performance

UUIDs are generally fast enough for most applications.

However, UUIDs are larger than numeric IDs.

A UUID occupies:

16 bytes

while:

BIGINT = 8 bytes
INTEGER = 4 bytes

The difference can affect:

• Index size
• Cache efficiency
• Storage
• Memory usage
• Foreign-key indexes

For small and medium applications, this difference is often not important.

At very large scale, it can become more relevant.

---

The Indexing Difference

Both approaches work well with B-tree indexes.

Auto-incrementing values generally have excellent index locality because new values tend to be inserted near the end of the index.

For example:

1
2
3
4
5
6
7

New rows normally append toward the end of the index.

Random UUIDs can be distributed throughout the B-tree:

8f...
1a...
c7...
3b...
e2...

This can cause more page splits and less locality under heavy insert workloads.

---

Why UUIDs Can Affect Insert Performance

Suppose you insert millions of random UUIDs.

The index might need to update different parts of the B-tree for each insert.

Conceptually:

Random UUID
     ↓
Different index location
     ↓
More page activity

With sequential numeric IDs:

1 → 2 → 3 → 4 → 5
         ↓
Mostly increasing index positions

This can provide better locality.

However, actual performance depends on the workload, PostgreSQL version, UUID generation strategy, hardware, and index design.

Don’t assume UUIDs will automatically make an application slow.

---

UUID Version Matters

Not all UUIDs have the same insertion characteristics.

Traditional UUIDv4 values are random.

Newer UUID versions such as UUIDv7 are designed to provide time-ordered properties while retaining UUID-style identifiers.

This can make UUIDv7 attractive for systems that want:

UUID benefits
+
Better insertion locality
+
Time-ordering characteristics

If your PostgreSQL version and application tooling support UUIDv7 appropriately, it can be worth considering for high-write workloads.

---

UUIDv4 vs UUIDv7

Feature	UUIDv4	UUIDv7
Randomness	High	Time-ordered structure
Sortable by creation time	No	Better suited
Index locality	Lower	Generally better
Distributed generation	Excellent	Excellent
Identifier format	UUID	UUID
High-write workloads	Works	Often attractive

UUIDv7 does not automatically replace numeric IDs in every system. It is simply another option with different trade-offs.

---

Security: UUID vs Auto-Increment

Suppose your API exposes:

/api/users/1
/api/users/2
/api/users/3

An attacker may easily guess that:

/api/users/4

exists.

This is called ID enumeration.

UUIDs are much harder to guess:

/api/users/550e8400-e29b-41d4-a716-446655440000

This can reduce casual enumeration.

However:

UUIDs are not a replacement for authorization.

Even if an ID is difficult to guess, your API must still verify that the requesting user is allowed to access the resource.

---

UUIDs in Public APIs

UUIDs can be useful when database identifiers are exposed publicly.

For example:

{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "name": "Oliver"
}

Compared with:

{
  "id": 12345,
  "name": "Oliver"
}

UUIDs make the identifier less obviously sequential.

This can be useful for public-facing APIs.

---

Auto-Increment IDs in Internal Systems

For internal applications where IDs aren’t exposed publicly, numeric IDs are often an excellent choice.

For example:

Internal database
    ↓
BIGINT primary key

You get:

• Compact identifiers
• Small indexes
• Excellent locality
• Simple debugging
• Easy joins

There is no reason to use UUIDs purely because they are considered more modern.

---

Distributed Systems

This is where UUIDs become particularly attractive.

Suppose you have:

Application A
Application B
Application C

all creating records independently.

With auto-increment IDs, coordinating unique IDs across databases can be difficult.

For example:

Database A → ID 100
Database B → ID 100

Now you have a collision if those records need to be combined.

With UUIDs:

Database A → UUID A
Database B → UUID B

each system can generate identifiers independently with an extremely low collision probability.

---

Microservices and UUIDs

Imagine a microservice architecture:

User Service
Order Service
Payment Service
Shipping Service

A shared UUID strategy can make identifiers easier to generate independently.

For example:

User ID
↓
UUID

Order ID
↓
UUID

Payment ID
↓
UUID

This can be useful when services need to create identifiers without coordinating through a single database sequence.

---

Database Sharding

UUIDs can also be useful in sharded systems.

For example:

Shard 1
Shard 2
Shard 3
Shard 4

Each shard can generate IDs independently.

With centralized auto-increment sequences, coordination can become more complicated.

UUIDs don’t solve every sharding problem, but they can simplify globally unique identifier generation.

---

UUID Storage in PostgreSQL

Always use PostgreSQL’s native:

UUID

type rather than storing UUIDs as text.

Prefer:

id UUID PRIMARY KEY

over:

id TEXT PRIMARY KEY

The native UUID type is more compact than textual representation and communicates the intended data type clearly.

---

Auto-Increment Storage

For large applications, prefer BIGINT when identifier growth could exceed the INTEGER range.

For example:

id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY

This provides a large identifier range while retaining the advantages of numeric keys.

---

UUID Foreign Keys

If your primary key is UUID, related foreign keys should also use UUID.

For example:

CREATE TABLE users (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    name TEXT NOT NULL
);

CREATE TABLE orders (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    user_id UUID NOT NULL REFERENCES users(id)
);

Don’t mix:

users.id → UUID
orders.user_id → TEXT

Use consistent types for relationships.

---

BIGINT Foreign Keys

The same principle applies to numeric IDs.

CREATE TABLE users (
    id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    name TEXT NOT NULL
);

CREATE TABLE orders (
    id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    user_id BIGINT NOT NULL REFERENCES users(id)
);

This keeps relationships consistent and efficient.

---

UUID Advantages

UUIDs offer several important advantages.

1. Globally Unique

They can be generated independently across systems.

2. Difficult to Guess

They don’t reveal simple sequential ordering.

3. Good for Distributed Systems

Multiple services can generate identifiers without relying on a central sequence.

4. Useful for Public APIs

They make IDs less obviously enumerable.

5. Easy Data Merging

Records from multiple databases can be combined with less concern about numeric ID collisions.

---

UUID Disadvantages

UUIDs also have trade-offs.

1. Larger

A UUID uses 16 bytes compared with 8 bytes for BIGINT.

2. Larger Indexes

Primary-key and foreign-key indexes can become larger.

3. Less Human-Friendly

This:

550e8400-e29b-41d4-a716-446655440000

is harder to read than:

12345

4. Random UUIDs Can Have Lower Locality

Random UUIDs can produce less predictable index insertion patterns.

5. Debugging Can Be Less Convenient

Numeric IDs are easier to recognize in logs and database queries.

---

Auto-Increment Advantages

Numeric IDs provide:

1. Small Storage

INTEGER and BIGINT are compact.

2. Smaller Indexes

Smaller keys generally mean smaller indexes.

3. Good Insert Locality

Sequential values work naturally with B-tree indexes.

4. Easy Debugging

It’s easier to say:

User 12345

than:

User 550e8400-e29b...

5. Simple Design

Identity columns are easy to understand and implement.

---

Auto-Increment Disadvantages

1. Predictable

IDs can be easy to enumerate if exposed publicly.

2. Centralized Generation

A sequence is associated with the database, which can complicate independent ID generation across multiple databases.

3. Harder Data Merging

Combining data from independent databases may require ID remapping or another global identifier.

4. Reveals Ordering

An ID such as:

100000

can reveal that many records may exist, although it does not necessarily represent an exact count.

---

Which Is Faster?

There is no universal winner.

For many traditional PostgreSQL workloads:

BIGINT

will generally have an advantage because it is smaller and sequential.

For distributed systems:

UUID

can be operationally simpler because IDs can be generated independently.

Performance should be measured against your actual workload.

---

Which Is Better for Large Tables?

If you have:

10 million rows

or:

100 million rows

the size of primary and foreign keys becomes increasingly relevant.

A BIGINT primary key is only 8 bytes.

A UUID is 16 bytes.

That difference can multiply across:

Primary key
Foreign keys
Indexes
Join tables
Secondary indexes

For extremely large relational systems, numeric IDs can therefore provide meaningful storage and cache-efficiency advantages.

---

Which Is Better for Microservices?

For microservices, UUIDs are often attractive.

Example:

Service A
   ↓
Generate UUID

Service B
   ↓
Generate UUID

Service C
   ↓
Generate UUID

No service needs to ask a central database for the next numeric ID.

This makes UUIDs particularly useful when entities may be created independently.

---

Which Is Better for a Monolith?

For a traditional monolithic application:

Application
     ↓
PostgreSQL

a BIGINT GENERATED ... AS IDENTITY primary key is often a simple and efficient choice.

There is no need to introduce UUID complexity unless you have a specific reason.

---

Which Is Better for Public APIs?

If database IDs are exposed directly in URLs, UUIDs can be a good option:

/api/orders/550e8400-e29b-41d4-a716-446655440000

But remember:

UUID
+
Authorization

is the correct security approach.

Don’t rely on unguessable IDs as your access-control mechanism.

---

Can You Use Both?

Yes.

A very useful pattern is to have an internal numeric primary key and a separate public identifier.

For example:

CREATE TABLE users (
    id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    public_id UUID NOT NULL DEFAULT gen_random_uuid() UNIQUE,
    name TEXT NOT NULL
);

Now:

id
→ Internal database relationships

public_id
→ Public API identifier

This gives you:

BIGINT performance
+
UUID-style public identifiers

However, it also adds another column and another unique index, so use this pattern when the separation provides real value.

---

UUID vs BIGINT Example

UUID Primary Key

CREATE TABLE products (
    id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
    name TEXT NOT NULL,
    price NUMERIC(10,2) NOT NULL
);

BIGINT Primary Key

CREATE TABLE products (
    id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
    name TEXT NOT NULL,
    price NUMERIC(10,2) NOT NULL
);

Both are valid PostgreSQL designs.

The choice depends on your requirements.

---

When Should You Choose UUID?

Choose UUID when:

✔ Multiple systems generate IDs
✔ You have a distributed architecture
✔ Data is created across multiple databases
✔ IDs are frequently exposed publicly
✔ You need globally unique identifiers
✔ You expect sharding or independent data generation

UUIDv7 can be especially interesting when you want UUID semantics with improved time-ordering characteristics.

---

When Should You Choose BIGINT?

Choose BIGINT when:

✔ PostgreSQL is the central source of ID generation
✔ You want compact indexes
✔ You have high insert volume
✔ Database performance and storage efficiency matter
✔ IDs are mostly internal
✔ You prefer simple database design

For many traditional applications, this is an excellent default.

---

What About INTEGER?

INTEGER can be perfectly suitable for smaller systems.

For example:

id INTEGER GENERATED ALWAYS AS IDENTITY PRIMARY KEY

But consider future growth.

If you expect the application to eventually contain hundreds of millions or billions of records, BIGINT gives you much more room.

Changing identifier types later can be expensive on large databases.

---

UUID vs Auto-Increment: Decision Guide

Use this simple decision process:

Do multiple systems generate IDs?
        │
       Yes
        ↓
      UUID
        │
       No
        ↓
Are IDs exposed publicly?
        │
       Yes
        ↓
UUID or separate public UUID
        │
       No
        ↓
Is maximum storage/index efficiency important?
        │
       Yes
        ↓
      BIGINT
        │
       No
        ↓
Choose based on architecture and preference

---

PostgreSQL UUID vs Auto-Increment Best Practices

Use Native Types

Prefer:

UUID

instead of:

TEXT

for UUIDs.

Prefer Identity Columns

For new PostgreSQL schemas, use:

GENERATED ... AS IDENTITY

rather than relying on the older SERIAL shorthand.

Use BIGINT for Large Numeric IDs

If you choose numeric IDs, BIGINT is often a safer long-term choice than INTEGER.

Keep Foreign Keys Consistent

UUID primary key → UUID foreign key.

BIGINT primary key → BIGINT foreign key.

Don’t Depend on IDs for Authorization

Always implement proper authorization.

Consider UUIDv7 for New UUID-Based Systems

If your tooling supports it, time-ordered UUIDs can be attractive for write-heavy systems.

---

Common Mistakes

Using TEXT for UUIDs

Avoid:

id TEXT

when the value is actually a UUID.

Prefer:

id UUID

---

Assuming Auto-Increment IDs Are Gapless

They aren’t guaranteed to be.

Don’t use them as business sequence numbers without a deliberate design.

---

Assuming UUIDs Are Always Slow

UUID performance depends on the UUID generation strategy and workload.

Measure before making assumptions.

---

Using UUIDs Only for Security

UUIDs can make enumeration harder, but they don’t replace authorization.

---

Using INTEGER Without Considering Growth

A database that outgrows the integer range can make migration more complicated.

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Final Verdict

There is no single best identifier type for every PostgreSQL application.

Choose BIGINT when you want:

Small identifiers
Smaller indexes
Excellent locality
Simple architecture
High storage efficiency

Choose UUID when you want:

Globally unique IDs
Distributed ID generation
Less predictable public identifiers
Easy cross-system data merging
Microservice-friendly identifiers

For many traditional applications, this is an excellent default:

id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY

For distributed applications or systems where identifiers are generated independently, UUID can be a better fit:

id UUID PRIMARY KEY DEFAULT gen_random_uuid()

And if you’re building a high-scale UUID-based system, consider whether UUIDv7 is appropriate for your PostgreSQL version and application stack.

The most important thing is to choose early and consistently, because changing primary-key types across a large database later can be a significant migration.

BIGINT is usually the simpler and more storage-efficient choice, while UUID is often the more flexible choice for distributed and public-facing systems.