ClickHouse vs OpenObserve for Logs, Metrics & Traces (2026)

ClickHouse is presented as a general-purpose columnar database that can support observability workloads but requires teams to build and operate components such as OTLP ingestion pipelines, signal correlation, dashboards, alerting, application-level access controls, SSO, and cluster scaling. OpenObserve is described as a purpose-built observability platform that provides native ingestion for logs, metrics, and traces, unified querying, dashboards, alerting, RBAC, and SSO on Parquet data stored in cloud object storage. The comparison emphasizes their differing architectures: self-hosted ClickHouse primarily relies on local-disk MergeTree storage and may require replication, coordination services, and resharding as data grows, while OpenObserve uses stateless compute with object storage intended to scale independently. Although both are characterized as having favorable compressed columnar storage economics, the text argues that the deciding cost is often the engineering effort required to turn raw ClickHouse into a full observability platform. It suggests ClickHouse may suit organizations with substantial in-house expertise and highly customized needs, whereas OpenObserve may suit teams seeking integrated observability capabilities and simpler scaling.

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