ApacheDruid vs ClickHouse

[ANANTHAN A]

Hi Team,

We are evaluating an analytics database for our use case and recently tested both Apache Druid and ClickHouse, focusing on query performance and data ingestion efficiency. Based on our findings, ClickHouse significantly outperforms Apache Druid in both query execution speed and data ingestion. However, Apache Druid stands out with its robust architecture, including superior horizontal scalability and advanced data management capabilities.

In summary, ClickHouse excels in performance, while Apache Druid offers a richer architecture, making each suitable for different priorities—whether it’s performance or scalability.

That said, if we can achieve efficient query execution and data ingestion in Apache Druid, we would prefer it due to its architectural strengths. Does anyone have insights or fine-tuning tips for optimizing Apache Druid to meet such performance requirements?

Looking forward to your thoughts and recommendations!

[John Kowtko]

Hi Ananthan,

Can you share some information about your workload?  A lot has to do with size and shape of data.  Druid relies a lot on parallelization for high end performance, so for smaller workloads it might be not be the most efficient fit ... but for larger and/or rapidly increasing workloads it is often a much better tool.

Thanks.   John

[John Adams]

You go straight to “in summary” here without actually identifying the hardware and test conditions that you ran your test on or how your Druid cluster was configured. 

It’s Impossible to make a judgment here with that understanding what exactly you were trying to do.

If you’ve never set up Druid before, and you push data at a commercial,  tested large scale system, vs a smaller bespoke Druid cluster, The commercial solution will win every time.

The real problem is what happens to cost and ROI. You will shall we say, lose to the house. Clickhouse and Snowflake get very expensive as data increases.

-j

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