Should I use ClickHouse instead of BigQuery for reporting?

Maybe — but it depends on what kind of reporting you mean.

Use ClickHouse if you want:

• Very fast interactive dashboards on large event/log data
• Lower cost for high query volumes
• Full control over infrastructure and tuning
• Real-time or near-real-time analytics with frequent reads
• A lot of pre-aggregated / denormalized data

Use BigQuery if you want:

• Minimal ops and easy setup
• Serverless scaling with little maintenance
• Strong integration with the Google Cloud ecosystem
• Ad hoc analytics over very large datasets without managing clusters
• Data warehousing with less concern about query tuning and storage layout

A practical rule of thumb

• ClickHouse is often better for product analytics / BI dashboards / event data where users hit the same tables constantly and latency matters.
• BigQuery is often better for batch reporting / exploratory analysis / warehouse-style workloads where convenience matters more than sub-second dashboard performance.

Things to compare before deciding

1. Query pattern

   • Many repeated dashboard queries → ClickHouse
   • Many one-off exploratory queries → BigQuery

2. Latency requirements

   • Sub-second to a few seconds → ClickHouse
   • Seconds to tens of seconds acceptable → BigQuery

3. Operations

   • Willing to manage clusters, schema design, merging, partitions → ClickHouse
   • Prefer managed/serverless → BigQuery

4. Cost model

   • ClickHouse can be cheaper at high usage
   • BigQuery can get expensive with lots of scanned data unless optimized

5. Data freshness

   • Both can be near real-time, but ClickHouse is often simpler for low-latency serving

Common pattern

A lot of teams use:

• BigQuery as the central warehouse
• ClickHouse as the serving layer for dashboards / customer-facing analytics

If you want, I can give you a decision matrix based on your data size, query volume, freshness needs, and cloud setup.