ClickHouse is an established open-source columnar OLAP database that has gained significant popularity due to its ability to handle large-scale real-time analytical workloads without compromising speed and efficiency. As users and organizations increasingly adopted ClickHouse for their data processing needs, they also shaped the open-source project with an ever growing list of integration capabilities turning it into a powerful data hub.
In this presentation, we'll display how ClickHouse's integration engines (a concept to provide virtual tables to remote data stores like OLTP systems and datalakes) empower real-world use-cases from simply importing data or ad-hoc querying to leveraging powerful algorithms to perform data grouping locally. We will also explore how external dictionaries can be leveraged to augment ClickHouse's querying capabilities by integrating with external data sources and look-up tables. Finally, we will cover ClickHouse’s materialized views, focusing on their role in precomputing and aggregating data to optimize query performance and provide continuous transformations on top of heterogeneous datasets.