An observability database aims to ingest, analyze and store Metrics, Tracing and Logging data.

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  1. 4608352 Bump vite from 6.3.4 to 6.3.6 in /ui (#763) by dependabot[bot] · 26 hours ago main
  2. a287c38 feat: improve trace query functionality (#762) by Gao Hongtao · 2 days ago
  3. 4d5813f - Add the TRACE Model to BydbQL and support distributed tracing with `WITH QUERY_TRACE` (#760) by Gao Hongtao · 2 days ago
  4. 174405b Fix the merging panic (#759) by Gao Hongtao · 3 days ago
  5. d613e58 Fix bugs time query range will not automatically update and add some new time query ranges (#757) by peachisai · 4 days ago

BanyanDB

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BanyanDB, as an observability database, aims to ingest, analyze and store Metrics, Tracing and Logging data. It's designed to handle observability data generated by observability platform and APM system, like Apache SkyWalking etc.

Introduction

BanyanDB, as an observability database, aims to ingest, analyze and store Metrics, Tracing, and Logging data. It's designed to handle observability data generated by Apache SkyWalking. Before BanyanDB emerges, the Databases that SkyWalking adopted are not ideal for the APM data model, especially for saving tracing and logging data. Consequently, There’s room to improve the performance and resource usage based on the nature of SkyWalking data patterns.

The database research community usually uses RUM Conjecture to describe how a database access data. BanyanDB combines several access methods to build a comprehensive APM database to balance read cost, update cost, and memory overhead.

Contact us

Documentation

Contributing

For developers who want to contribute to this project, see the Contribution Guide.

License

Apache 2.0 License.