etcd-io/dbtester

Distributed database benchmark tester

Hosted by Cloud Native Computing Foundation · part of Linux Foundation

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etcd-io/dbtester has 250+ stars and 40+ forks on GitHub, is written in Go, and was last pushed on Sep 25, 2023. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 4 minutes ago
Added to GitGenius on October 15th, 2026
Created on March 16th, 2016
Open Issues & Pull Requests: 5 (+0)
GitHub issues: Enabled
Number of forks: 47
Total Stargazers: 289 (+0)
Total Subscribers: 21 (+0)

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Detailed Description

dbtester is a distributed database benchmark tester that measures and compares the performance of key-value datastores including etcd, Zookeeper, Consul, zetcd, and cetcd.

The tool addresses the need to understand how distributed databases perform under realistic load conditions. It works by deploying database agents across multiple machines, running coordinated client workloads against each database, collecting system metrics during execution, and analyzing the results to produce performance comparisons. The benchmark framework can simulate various scenarios such as writing millions of entries with concurrent clients and measuring throughput, latency, and system behavior under stress.

Teams evaluating distributed key-value stores for consistency and performance characteristics should consider this tool. It suits projects that need empirical data on how etcd, Zookeeper, and Consul behave at scale, particularly when deciding between these systems for a production deployment. The README notes that for etcd specifically, the etcd benchmark tool is recommended as an alternative. The project publishes detailed test results including performance analysis across different database systems and configurations, allowing direct comparison of throughput and latency profiles.

Development activity shows consistent focus on maintaining benchmark infrastructure and test result documentation. The project includes components for database agents, client control, system metrics collection, and data analysis with visualization capabilities. Test results are systematically archived and made publicly available for reference.