Real-Time Analytics Stack (Kafka, ClickHouse, Grafana, dbt) overview

A real-time analytics architecture: Apache Kafka ingests high-volume event streams from applications and infrastructure, ClickHouse serves as the columnar OLAP database optimized for sub-second analytical queries over billions of rows, Grafana provides dashboarding and alerting, and dbt models transformations within the analytics layer. Kafka decouples event producers from consumers, enabling fan-out to multiple downstream systems. ClickHouse's MergeTree engine family provides real-time inserts with immediate query availability -- unlike batch-oriented warehouses. Materialized views in ClickHouse pre-aggregate common query patterns. Grafana connects directly to ClickHouse via plugin and renders live dashboards with auto-refresh. dbt manages the transformation layer, turning raw event tables into clean analytical models with tests and documentation. This stack is used for product analytics, operational dashboards, ad-tech bidding analytics, and any workload requiring low-latency queries over streaming data.