OpenObserve vs Elasticsearch: Performance Benchmarking at 1.1 TB Scale

A benchmark comparing OpenObserve and Elasticsearch at a 1.1 TB scale reveals significant performance differences, particularly favoring OpenObserve in terms of storage efficiency, CPU utilization, RAM usage, and query performance. During ingestion, Elasticsearch dropped 62% of the data due to schema mapping conflicts, consumed 10 times more RAM, and operated at 96% CPU, whereas OpenObserve accepted all data, compressed it by 9.5 times, and maintained a CPU usage of 15%, resulting in an 87 times cheaper storage cost. In query performance, OpenObserve outperformed Elasticsearch in 14 out of 15 tests, being up to 32 times faster in aggregations, while Elasticsearch only excelled in COUNT(*) queries by 1.5 times. The study highlights OpenObserve's architectural advantages, such as its automatic schema handling and columnar storage, making it more suitable for handling Kubernetes-format log workloads at scale, while Elasticsearch's schema rigidity and high resource consumption present challenges.

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