We use both ClickHouse and Databricks for different data analytics use cases. 

A recurring question is often asked: when to use each platform. 


I’ve created the decision tree below to help developers choose, and I would be happy to hear your thoughts.


Use ClickHouse when:

  • You need sub-second analytics
  • You need an OLAP database for dashboards / APIs
  • Data is structured, columnar, event-based, or time-series
  • You want high-performance SQL
  • You want to query real-time streaming data
  • You need a high-throughput analytics store (10M–100M rows/sec)

Use Databricks when:

  • You need ETL/ELT pipelines, Spark processing, or heavy batch jobs
  • You are building a Delta Lake, need to use versioning, or ML workflows
  • You need to process very large raw datasets (TB–PB scale)
  • Workloads include machine learning, notebooks, or data science