⚡ Serverless Computing Platforms in Hungary

Serverless computing platforms allow developers to run backend code without managing servers, using event-driven execution models where functions are triggered by HTTP requests, database changes, or other events.

Hungary is a Central European country with a population of around 9.6 million people.

According to our research, serverless computing platforms are detected on 0.3% of websites from Hungary.

⭐ Most Popular in 2026

The following chart shows the top serverless platforms in Hungary in 2026, based on market share.

The most popular is AWS Lambda with an impressive share of 50%, followed by Google Cloud Run with 25.9% and CloudFront Functions with 15.5%.

🚀 Highlights

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

✨ Best Serverless Platforms

Below is a more detailed list of 5 serverless platforms used on sites from Hungary, ranked by their market share.

RankNameMarket share
1
AWS Lambda
Seattle, Washington, United States

A serverless compute service from Amazon Web Services that runs code in response to events and automatically manages the underlying infrastructure.

Free tier
2
Google Cloud Run
Mountain View, California, United States

A pay-as-you-go serverless service that runs containerized applications without managing servers or infrastructure.

Free tier
3
CloudFront Functions
Seattle, Washington, United States

A serverless edge compute feature of Amazon CloudFront that runs lightweight JavaScript code at edge locations to customize HTTP requests and responses with minimal latency.

Free tier$$$
4
Vercel Serverless Functions
San Francisco, California, United States

A serverless compute feature that runs backend code on demand without managing infrastructure.

Free$20+/user/month
5
Azure Functions
Redmond, Washington, United States

An event-driven, serverless compute platform from Microsoft, hosted on the Microsoft Azure cloud.

👉 See Also

🗃️ About This Data