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commit 453b51304039c335bf0583854d873122747be6fc Author: 吴晟 Wu Sheng <[email protected]> AuthorDate: Mon Dec 15 16:24:43 2025 +0800 Revise BanyanDB documentation for clarity and detail Updated the BanyanDB section to enhance clarity and detail regarding its performance benchmarks and resource optimization. Added links to benchmark documentation for further reference. --- docs/en/setup/backend/backend-storage.md | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/docs/en/setup/backend/backend-storage.md b/docs/en/setup/backend/backend-storage.md index 6542770eab..08d616fd95 100644 --- a/docs/en/setup/backend/backend-storage.md +++ b/docs/en/setup/backend/backend-storage.md @@ -10,12 +10,14 @@ storage: ## BanyanDB - Native APM Database - [BanyanDB](storages/banyandb.md) -BanyanDB is a native-built SkyWalking database, which can completely focus on SkyWalking use cases. -It has demonstrated significant potential for performance improvement and reduced resource usage requirements. It indicates 5x less memory usage, -1/5 disk IOPS, 1/4 disk throughput, and 30% less disk space, albeit with a slightly higher CPU trade-off, compared to Elasticsearch. - -In benchmark testing, a BanyanDB cluster with 2 liaison nodes and 2 data nodes (each with 2 cores and 4GB memory) successfully handled sustained high-throughput workloads: -ingesting over 571,000 metric data points, 151,000 stream records, and 6,600 traces (133,200 spans) per minute. Query performance remained responsive with median latencies of 26ms for metrics (p99: 288ms), 7ms for streams (p99: 72ms), and 436ms for traces (p99: ~1.1s) under concurrent read/write operations. +BanyanDB is a native-built SkyWalking database that focuses entirely on SkyWalking use cases. +BanyanDB demonstrates significant potential in improving performance and optimizing resource utilization. +In typical deployment scenarios involving around 200 services and 200+ calls per second, a cluster configured with 2 liaison nodes and 2 data nodes—each equipped with 4 vCPUs and 8 GB memory—delivers stable and efficient performance. +BanyanDB also supports full tracing sampling, providing trace collection capabilities up to 100%, ensuring comprehensive observability without compromising system stability. + +For the latest performance benchmarks of **BanyanDB**, please refer to the following sections: +- [**Single‑Model Benchmark (Trace / Log / Measure / Property)**](https://skywalking.apache.org/docs/skywalking-banyandb/next/operation/benchmark/benchmark-single-model/) — evaluates individual data models in isolation. +- [**Hybrid Scenario Benchmark — Realistic workloads for typical SkyWalking use cases**](https://skywalking.apache.org/docs/skywalking-banyandb/next/operation/benchmark/benchmark-hybrid/) — simulates mixed observability data ingestion and query scenarios. ## SQL database - [MySQL and its compatible databases](storages/mysql.md)
