Log data, as it grows in importance and its sheer volume – is increasingly looking like analytical data. Small, semi-structured datasets in high volumes, critical insights to be captured from the data – the boundary between a log and an analytical event is as thin as ever. 

Organisations are adapting by switching to OLAP stores like ClickHouse for their log storage. But OLAP platforms are essentially databases, built for BI-type use cases. This leaves a huge gap in the overall experience. Most important logging features like alerts, correlation, deep diving into an incident, and much more are not at all available.