Tranco Top List

Websitehttps://tranco-list.eu/
CategoryDomain Rankings

The Tranco Top List is a research-grade domain ranking designed to provide a stable and manipulation-resistant measure of domain popularity. Developed by researchers at KU Leuven university in Belgium, it aggregates multiple independent domain ranking sources into a single composite list. We use Tranco as one of several domain popularity signals displayed on domain and DNS lookup pages across robtex.com and dns.ninja.

Source:Tranco Top List

What is Tranco?

Tranco was created to address well-documented problems with existing domain ranking lists. Academic researchers found that popular lists like the Alexa Top 1M were volatile, easy to manipulate, and inconsistent across days. A domain could jump tens of thousands of positions between daily snapshots, making them unreliable for security research and reproducible experiments.

The Tranco methodology solves these problems by:

  • Aggregating multiple sources - Combining rankings from Majestic, Cisco Umbrella, Chrome UX Report, and other lists. No single source can dominate the final ranking.
  • Averaging over time - Using a rolling window (typically 30 days) to smooth out daily volatility. A domain must be consistently popular, not just briefly trending.
  • Filtering noise - Removing subdomains, pay-level domains, and other artifacts that inflate rankings in the source lists.
  • Resisting manipulation - Because it combines multiple independent methodologies (backlinks, DNS queries, browser usage), gaming one source has minimal effect on the final rank.

The result is a list where position changes reflect genuine shifts in a domain's internet presence rather than measurement noise or deliberate manipulation. This is why Tranco has become the standard domain ranking in academic security research, cited in hundreds of peer-reviewed papers.

The project is open source and the lists are freely downloadable, with reproducible generation from publicly documented parameters.

How We Use This Data

Tranco serves as one of five domain popularity signals on our domain and DNS lookup pages on robtex.com and dns.ninja. When you look up a domain, we display its Tranco rank alongside its rank from each individual source list.

Because Tranco already performs aggregation and smoothing, it functions as a high-quality composite signal. A domain with a strong Tranco rank is almost certainly a well-established site with consistent presence across multiple independent metrics. Domains that appear in Tranco but not in some individual source lists are still likely significant -- the aggregation methodology captures domains that individual lists may miss.

We show both the Tranco composite rank and the individual source ranks so users can understand the full picture. A domain ranking highly in Tranco but missing from one specific source suggests it is popular through channels that particular source does not measure well.

FAQ

Why use Tranco when you already import the individual source lists?
Tranco's value lies in its aggregation methodology. It applies time-averaging, deduplication, and cross-source normalization that we would otherwise need to implement ourselves. Having both the composite Tranco rank and individual source ranks gives users the best of both worlds: a reliable summary and the ability to drill into where a domain's popularity comes from.
How is Tranco different from the old Alexa Top 1M?
Alexa ranked domains by estimated traffic from its browser toolbar panel, which was small and biased toward certain demographics. Alexa was volatile (ranks shifted dramatically day-to-day), easy to manipulate (toolbar installs could inflate rankings), and was eventually shut down in 2022. Tranco addresses all of these weaknesses through multi-source aggregation and time averaging.
Can a domain be ranked in Tranco but not in any individual source list?
In practice, no. Tranco derives its ranking from the source lists, so a domain must appear in at least one source to be included. However, a domain might appear in Tranco at a different position than in any individual source, because the aggregation and time-averaging process redistributes ranks based on cross-source consistency.