StreamRooms's analysis tools run on a data infrastructure that can query hundreds of millions of chat messages and tens of thousands of channels in real time. Even at this scale, results are produced in seconds.
In an ever-expanding archive, the system tracks more than 150 million chat messages and more than 27,000 channels. This data underpins every analysis feature, such as bot detection, viewer analytics and chatter tracking.
The accuracy of features like bot detection and viewer analytics depends on the depth of historical data the system has. To determine a channel's "normal" participation rate, you need the real behavior patterns from its past streams; that's only possible with a large-scale, continuously updated data archive.
Chat messages and viewer data are collected in real time while streams are running. This keeps analysis results always up to date.
StreamRooms's data infrastructure collects public chat and stream data on the Kick platform to feed its analysis tools.
The data infrastructure is specifically designed for large-scale, real-time queries; analysis results are produced in seconds.
The system keeps an ever-expanding archive; enough historical depth is stored to assess channels' past behavior patterns.
Setup takes a few minutes and needs no extra hardware.
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