Some common ClickHouse use cases and verticals shown below. Basically any case where you have relatively structured data, very large fact tables, and a need for

Some common ClickHouse use cases and verticals shown below. Basically any case where you have relatively structured data, very large fact tables, and a need for low latency response. Names of companies that have given public talks are shown. * Analyzing netflow logs (network management, numerous users) * Content delivery (Mux.com) * Web analytics (ContentSquare, CloudFlare) * Generating optimized parameters for real time ad bidding (various, not too many recent talks on this) * Log management and system observability (surprisingly common across industries-Sentry, Cloudflare, Uber) * Valuing assets from market data, e.g. tick data (financial services, not many companies will discuss publicly) Druid is used for some of these. I don't know that much about Pinot, hence cannot comment there.