|Jan 2020 Rank||Dec 2019 Rank||System||Jan 2020 Score||Dec 2019 Score|
The Feature Store Ranking is a list of feature store systems for ML ranked by their current popularity. The popularity of a feature store is measured using the following criteria:
- Frequency of links/mentions on websites, measured as number of results in search engines queries. Google allows us to count searches for <system> together with “feature Store”, e.g., “Michelangelo” and “feature store”.
- Search interest. The frequency of searches using Google Trends.
- Technical discussion on Stack Overflow. The number of related questions and the number of interested users.
- Interest in Twitter. The number of tweets that reference the system.
We calculate normalize and average the different criteria when calculating the popularity of a system. The score can be seen as a measurement for the system’s popularity (3X score, means roughly 3X times the interest in a system). We are not able to count the number of installations.