Use cases

ClickHouse is suitable for use as both a primary data store and as an analytics layer. Its columnar architecture, vectorized processing, and cloud-native design make it uniquely suited for analytical workloads that require both speed and scale. If you are choosing a database for an application, start with Choose a service for your workload. It maps analytical results, transactional state, observability, and local analysis to the relevant services and explains when a mixed workload needs more than one database.

Use case	TLDR
Real-time analytics	Sub-second queries on billions of rows as data arrives. Ideal for customer-facing dashboards, live leaderboards, and any product feature that reads from a continuously updating event stream.
Observability	Ingest and query logs, metrics, and traces in a single ClickHouse database via ClickStack. Eliminates the three-pillar silo problem and gives correlated, full-fidelity analysis without pre-aggregation.
Data warehousing	Pair ClickHouse with open table formats (Iceberg, Delta Lake, Hudi) on object storage to get ACID transactions, schema enforcement, and warehouse-grade query performance without locking your data away.
Agentic analytics	AI agents demand high concurrency and full-fidelity data simultaneously. ClickHouse converges real-time analytics, data warehousing, and observability into a single platform that agents can query directly via MCP or natural language interfaces.

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