DEV Community: Farasat Ali Shahzad

UUID vs ULID vs NanoID: Which Identifier Should You Use in 2026?

Farasat Ali Shahzad — Sun, 14 Jun 2026 17:39:45 +0000

A few years ago, choosing an ID format was easy.

Most of us generated a UUID, stored it in the database, and moved on.

Today things are different.

Modern applications care about:

Database performance
URL friendliness
Sortability
Distributed systems
Storage efficiency

That's why developers are increasingly looking at alternatives like ULID and NanoID.

If you're building APIs, SaaS products, mobile apps, event-driven systems, or microservices, understanding the differences can save you from painful migrations later.

Let's break down the three most common options.

The Problem We're Trying to Solve

Every system needs unique identifiers.

Traditionally, databases used auto-increment integers:

```sql id="s6v1j0"
1
2
3
4
5




This works until you need:

* Multiple servers
* Offline clients
* Distributed systems
* Public URLs
* Security against enumeration attacks

That's where globally unique identifiers become useful.

---

## UUID: The Industry Standard

UUID stands for Universally Unique Identifier.

Example:



```text id="t0r7gq"
550e8400-e29b-41d4-a716-446655440000

Most developers have seen these everywhere.

Benefits:

✅ Widely supported

✅ Available in almost every programming language

✅ Extremely low collision probability

✅ Battle-tested for decades

Drawbacks:

❌ Long and bulky

❌ Not human-friendly

❌ Random UUIDs fragment database indexes

❌ Difficult to sort chronologically

A table with millions of randomly generated UUIDs can create index fragmentation because new records are inserted all over the index tree instead of at the end.

For small projects this rarely matters.

For large-scale systems it absolutely does.

ULID: UUID With Better Ordering

ULID stands for Universally Unique Lexicographically Sortable Identifier.

Example:

```text id="x3r89v"
01JZ2M9Y6S1AWQKPVKQG6M6T4A




ULIDs solve one of UUID's biggest weaknesses.

They contain a timestamp component.

This means:



```text id="m4pnzk"
ULID A < ULID B

also means:

```text id="84gq0w"
Created Earlier < Created Later




without requiring an additional timestamp field.

Benefits:

✅ Time sortable

✅ Better database locality

✅ URL friendly

✅ Shorter than UUID

✅ Easier to read

Drawbacks:

❌ Slightly newer ecosystem

❌ Not as universally supported as UUID

❌ Timestamp portion can reveal creation timing

For many SaaS applications, ULID offers a very attractive balance between uniqueness and database efficiency.

---

## NanoID: Tiny but Powerful

NanoID was created as a lightweight alternative.

Example:



```text id="zzcb8w"
V1StGXR8_Z5jdHi6B-myT

Instead of 36 characters like a UUID, NanoID often uses around 21 characters.

Benefits:

✅ Very small

✅ URL safe

✅ Fast generation

✅ Excellent for frontend applications

✅ Lower storage requirements

Drawbacks:

❌ Not naturally sortable

❌ Requires length configuration decisions

❌ Less standardized across ecosystems

NanoID has become especially popular in JavaScript and frontend frameworks.

Many modern React, Vue, and Node.js projects use it by default.

Database Performance Differences

This is where things become interesting.

UUID

Random insertion pattern:

```text id="4syvfk"
7
2
10
1
9




Database indexes become fragmented over time.

### ULID

Chronological insertion pattern:



```text id="kbhvkk"
1
2
3
4
5

New records tend to be appended naturally.

This generally produces healthier indexes.

NanoID

Behaves similarly to random UUIDs unless custom strategies are used.

What About Security?

Many developers assume identifiers are security features.

They are not.

However, identifiers can help reduce enumeration attacks.

Compare:

```text id="x22vt5"
/users/1
/users/2
/users/3




versus:



```text id="5nql7v"
/users/01JZ2M9Y6S1AWQKPVKQG6M6T4A

The second approach makes guessing records significantly harder.

All three options are better than sequential IDs for public-facing resources.

Which One Should You Choose?

Choose UUID if:

You want maximum compatibility
You're working in enterprise environments
Existing systems already use UUIDs
Simplicity is more important than optimization

Choose ULID if:

You're building a SaaS product
You care about database performance
You want chronological sorting
You're designing a new system from scratch

Choose NanoID if:

You're building frontend-heavy applications
You want shorter URLs
Bundle size matters
You need compact identifiers

What I Use Today

If I were starting a new SaaS project in 2026, I would probably choose ULID.

Not because UUID is bad.

UUID remains a fantastic choice.

But ULID provides:

Global uniqueness
Better database behavior
Built-in ordering
Cleaner URLs

without adding much complexity.

For frontend-only applications, NanoID is also extremely attractive due to its compact size.

Want to Experiment with UUIDs Yourself?

While researching identifier strategies for APIs, databases, and distributed systems, I found it useful to generate and compare different ID formats directly rather than relying only on documentation.

If you're evaluating which identifier works best for your project, these resources may be useful:

Everything runs locally in the browser, so you can experiment with different identifier formats without sending data to a server.

One thing that becomes obvious when testing them side by side is how differently they behave in terms of readability, sortability, URL-friendliness, and database indexing. Seeing actual generated IDs often makes the trade-offs much easier to understand than reading specifications alone.

Final Thoughts

There isn't a single "best" identifier.

Each option solves a slightly different problem.

The mistake many teams make is choosing an identifier format without considering future scale, database behavior, and developer experience.

If your application is expected to grow beyond a small side project, spending 30 minutes evaluating UUID, ULID, and NanoID today can save weeks of migration work later.

What are you using in your projects today?

UUID, ULID, NanoID—or something else entirely?

YAML vs JSON: The Hidden Problems Most Developers Discover Too Late

Farasat Ali Shahzad — Sun, 14 Jun 2026 17:13:20 +0000

For years, I assumed YAML was simply a more readable version of JSON.

Many developers do.

Then I spent time debugging configuration files across Docker, Kubernetes, CI/CD pipelines, GitHub Actions, and infrastructure deployments. That's when I learned that YAML's flexibility is both its greatest strength and its biggest trap.

If you've ever spent an hour chasing a configuration bug caused by indentation, unexpected type conversion, or a mysterious parser error, this article is for you.

Why Developers Love YAML

YAML was designed to be human-friendly.

Compare this JSON:

{
  "name": "web-api",
  "port": 8080,
  "enabled": true,
  "hosts": [
    "api.example.com",
    "api2.example.com"
  ]
}

with the equivalent YAML:

name: web-api
port: 8080
enabled: true

hosts:
  - api.example.com
  - api2.example.com

Most people find YAML easier to read.

That's why tools like:

Kubernetes
Docker Compose
GitHub Actions
Ansible
CircleCI

all heavily rely on YAML.

Why JSON Continues to Dominate APIs

JSON won the web.

Almost every modern API uses JSON because it is:

Simple
Predictable
Strictly structured
Easy for machines to process

A parser reading JSON doesn't need to guess much.

The syntax rules are explicit.

For example:

{
  "enabled": true
}

There is very little ambiguity.

This predictability is one reason JSON became the standard format for API communication.

The YAML "Norway Problem"

One of the strangest YAML issues is known as the Norway Problem.

Consider this YAML:

country: NO

Depending on the parser and configuration, NO might be interpreted as:

false

instead of the country code for Norway.

The same can happen with values such as:

yes
no
on
off

Some YAML parsers automatically convert them into boolean values.

That means:

feature: on

might become:

feature: true

without you intending it.

Many production bugs have been caused by this behavior.

Indentation Can Break Everything

JSON ignores visual formatting.

YAML does not.

This works:

services:
  web:
    image: nginx

This does not:

services:
 web:
   image: nginx

A single misplaced space can invalidate an entire configuration file.

Anyone who has worked with Kubernetes manifests has probably experienced this frustration.

Security Risks Most Teams Ignore

A surprising number of developers assume YAML is just a text format.

The reality is more complicated.

Certain YAML parsers support advanced object serialization features.

Historically, insecure parser configurations have allowed:

Arbitrary object creation
Remote code execution
Unsafe deserialization attacks

This is one reason security-conscious teams often prefer JSON when exchanging data between systems.

JSON's simpler structure reduces the attack surface.

JSON Is Boring — And That's Good

One thing I've learned over time:

Boring technologies are often the safest technologies.

JSON is intentionally limited.

You can't add comments.

You can't create complex references.

You can't do fancy tricks.

And that's exactly why JSON behaves consistently across languages, frameworks, and platforms.

When reliability matters, boring wins.

When YAML Is the Better Choice

YAML shines when humans frequently edit the file.

Examples include:

Kubernetes manifests
Docker Compose
CI/CD pipelines
Infrastructure as Code
Application configuration files

In these scenarios, readability matters more than strict machine efficiency.

When JSON Is the Better Choice

JSON is usually the better option for:

APIs
Data exchange
Microservices communication
Browser applications
Logging systems
Event streams

If a machine writes the file and another machine reads it, JSON is often the safer choice.

Performance Differences

Many developers ask:

"Which is faster?"

In most real-world scenarios:

JSON parsers are generally faster.

Why?

Because JSON has:

Simpler grammar
Fewer parsing rules
Less ambiguity

The performance difference usually won't matter for small files, but it becomes noticeable at scale.

My Rule of Thumb

After working with both formats across multiple projects, my rule is simple:

Humans editing configuration → YAML
Machines exchanging data → JSON

This approach avoids most of the headaches while preserving the strengths of both formats.

Want to Experiment with YAML and JSON Yourself?

While researching and testing the examples in this article, I found it useful to switch between formats and compare their behavior directly rather than relying only on theory.

If you're working with configuration files, APIs, Docker Compose, Kubernetes manifests, or CI/CD pipelines, these browser-based resources may be useful:

Everything runs locally in the browser, so you can experiment with sample payloads without sending data to a server.

Final Thoughts

YAML isn't bad.

JSON isn't outdated.

They're tools designed for different jobs.

The problem happens when we use one where the other would have been a better fit.

Understanding the tradeoffs can save hours of debugging and help prevent subtle production issues that are surprisingly difficult to diagnose.

What has been your most frustrating YAML or JSON bug?

I'd love to hear your stories in the comments.