commit | 3f5739721911289beca24a80edcdc149f2c40530 | [log] [tgz] |
---|---|---|
author | Gao Hongtao <hanahmily@gmail.com> | Mon Apr 29 20:28:47 2024 +0800 |
committer | GitHub <noreply@github.com> | Mon Apr 29 20:28:47 2024 +0800 |
tree | a80db8c5a0442069b93f3434a0a2c6a71cf5a2f3 | |
parent | a43822e3f3e7e3351b44a02f133146392ab8bbf1 [diff] |
Bump Go Node and Dependencies (#441) * Validate resource * Update linter * Bump go to 1.22 * bump node and ui dependencies * Fix NPE when no index filter * Update Node version --------- Signed-off-by: Gao Hongtao <hanahmily@gmail.com>
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.
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.
Request to join SkyWalking slack
mail to the mail list(dev@skywalking.apache.org
), we will invite you in.[CN] Request to join SkyWalking slack
mail to the mail list(dev@skywalking.apache.org
), we will invite you in.For developers who want to contribute to this project, see the Contribution Guide.