# How Medium Powers Real-Time Recommendations at 1M OPS

DevFeed: [How Medium Powers Real-Time Recommendations at 1M OPS](<https://devfeed.tech/articles/how-medium-powers-real-time-recommendations-at-1m-ops-4879.md>)

Original publisher: [Read original article](<https://www.scylladb.com/2026/08/11/medium-real-time-recommendations/>)

Author: Cynthia Dunlop

Published: 2026-08-11T16:40:45Z

Content type: article

Language: en

Sources: [ScyllaDB](<https://devfeed.tech/sources/scylladb.md>)

Topics: [real-time](<https://devfeed.tech/topics/real-time.md>), [scylladb](<https://devfeed.tech/topics/scylladb.md>), [data](<https://devfeed.tech/topics/data.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Software](<https://devfeed.tech/topics/software.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [data](<https://devfeed.tech/tags/data.md>), [inference](<https://devfeed.tech/tags/inference.md>), [models](<https://devfeed.tech/tags/models.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [recommendation-system](<https://devfeed.tech/tags/recommendation-system.md>), [scale](<https://devfeed.tech/tags/scale.md>), [scylladb](<https://devfeed.tech/tags/scylladb.md>), [user-stories](<https://devfeed.tech/tags/user-stories.md>)

## AI overview

The article explains how Medium's ScyllaDB-based feature store supports real-time recommendations. It describes processing user activity and new articles, storing features for recommendation models, and addressing data-modeling challenges as the system scaled to 1 million operations per second.

## Source excerpt

Inside Medium's move from relational features to list features in its ScyllaDB-based feature store "Keep readers reading" is the not-so-simple goal of Medium's recommendations system. To predict what's most likely to appeal to a particular reader at any given time, Medium continuously processes user activity signals (stories read, recommendations shown, follows, likes, etc.). It then immediately correlates that with the steady stream of new articles, which is estimated at millions per month. Smart models and good inference logic are required, but that's not enough. The data must be stored and retrieved quickly enough to remain relevant while the user is [...]