⚡ Tech Stack in Thailand

A technology stack, also known as a software stack or development stack, is a set of programming languages, technologies and tools that are used to build and run software or a website.

Thailand is a Southeast Asian country with a population of around 72 million people.

According to our statistics, tech stacks are detected on 19.3% of websites from Thailand.

⭐ Most Popular in 2026

The following chart shows the top tech stacks on websites in Thailand in 2026, based on market share.

The most popular is LEMP with an impressive share of 50%, followed by LAMP with 22.1% and Microsoft with 13.9%.

🚀 Highlights

Here is a list of the top tech stacks that are more popular in Thailand than worldwide.
Differences between global and country rankings are shown in parentheses.

✨ Best Tech Stacks

Below is a more detailed list of 10 tech stacks used on sites from Thailand, ranked by their market share.

RankNameMarket share
1
LEMP

An open-source web application stack consisting of Linux, Nginx, MySQL, and PHP, Perl, or Python.

2
LAMP

An open-source web application stack consisting of Linux, Apache, MySQL, and PHP, Perl, or Python.

3
Microsoft
Redmond, Washington, United States

A set of software products and technologies from Microsoft.

4
Jamstack
San Francisco, California, United States

A web development architecture pattern and solution stack based on JavaScript, APIs, and Markup.

5
WIMP

A web application stack consisting of Windows, IIS, MySQL, and PHP, Perl, or Python.

6
MERN

An open-source web application stack consisting of MongoDB, Express.js, React.js, and Node.js.

7
MEVN

An open-source web application stack consisting of MongoDB, Express.js, Vue.js, and Node.js.

8
WAMP

A software stack consisting of Windows, Apache, MySQL, and PHP, Perl, or Python.

9
MEAN

An open-source web application stack consisting of MongoDB, Express.js, Angular/AngularJS, and Node.js.

10
LAPP

An open-source web application stack consisting of Linux, Nginx, PostgreSQL, and PHP, Perl, or Python.

👉 See Also

🗃️ About This Data