0 views collected around this technical thread.
This article compares Elasticsearch and ClickHouse as log‑search solutions, detailing their architectures, Docker‑compose deployments, data‑ingestion pipelines with Vector, query syntax differences, and benchmark results that show ClickHouse generally outperforms Elasticsearch in speed and aggregation efficiency.
Tencent’s Cloud Log Service augments Lucene with a dedicated time‑series index—using timestamp ordering, a secondary index, reverse binary search, and histogram optimization—to cut log query complexity, delivering up to 40‑50× faster responses, higher concurrency, and markedly better performance than traditional ELK‑style and competing cloud log solutions.
This article compares Elasticsearch and ClickHouse in architecture, query capabilities, and performance for log search workloads, presenting Docker‑compose setups, data ingestion pipelines, sample queries, and benchmark results that show ClickHouse generally outperforms Elasticsearch, especially in aggregation scenarios.
Over seven years, Pinterest’s monitoring team built and refined a three‑pronged observability platform—time‑series metrics, log search, and distributed tracing—scaling from a single‑machine system to handling millions of data points per second across tens of thousands of AWS VMs, while addressing reliability, cost, and usability challenges.
This article chronicles Pinterest's seven‑year evolution from a single‑machine time‑series monitor to a multi‑component system that integrates metrics, log search, and distributed tracing, sharing architectural choices, scaling challenges, and lessons learned for building reliable, high‑performance operations platforms.