Does ClickHouse support frequent, concurrent queries?

Yes. ClickHouse is designed for real-time analytical applications that can serve external users directly. It can serve analytical queries with low latency (less than 10 milliseconds) and high concurrency (exceeding 10,000 queries per second) on petabyte-scale databases, combining historical data and real-time insertions.

What makes high concurrency possible

Fast individual queries are the foundation of high QPS. The less work each query does, the more queries a server can run at once. The main features that reduce per-query work are:

• The sparse primary index of the MergeTree table engine family, which skips reading data that doesn’t match the query.
• Caches such as the query cache, which serves repeated SELECT queries directly from cached results.
• Projections, which precompute data at insert time and can be selected automatically by ClickHouse, and materialized views, which store precomputed results in a separate target table that queries can read directly.

Controlling and limiting concurrency

By default, ClickHouse OSS doesn’t limit the number of concurrent queries. ClickHouse Cloud sets max_concurrent_queries_for_all_users to 1000 by default. You can configure limits at several levels:

• max_concurrent_queries limits the total number of concurrently executed queries on the server. max_concurrent_insert_queries and max_concurrent_select_queries apply the same limit to INSERT and SELECT queries separately. All three default to 0 (unlimited).
• max_concurrent_queries_for_user and max_concurrent_queries_for_all_users limit concurrency per user or across all users.

Isolating workloads

To keep concurrent workloads from interfering with each other, ClickHouse provides:

• Workload scheduling to regulate how CPU, memory, and IO are shared between workloads.
• Quotas to limit resource usage per user over a time interval.
• Restrictions on query complexity to guard against individual queries consuming excessive resources.
• Built-in role-based access control to scope what each user can query.

Together, these make ClickHouse suitable as a serving layer on top of analytical data.