Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Leveldb | 32,273 | 3 | a day ago | 1 | February 27, 2018 | 269 | bsd-3-clause | C++ | ||
LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. | ||||||||||
Fastify | 26,867 | 1,131 | 1,764 | a day ago | 235 | September 14, 2022 | 80 | other | JavaScript | |
Fast and low overhead web framework, for Node.js | ||||||||||
Fasthttp | 19,315 | 645 | 1,957 | a day ago | 175 | September 03, 2022 | 70 | mit | Go | |
Fast HTTP package for Go. Tuned for high performance. Zero memory allocations in hot paths. Up to 10x faster than net/http | ||||||||||
Benchmarkdotnet | 8,838 | 1,125 | 94 | 19 days ago | 57 | August 26, 2022 | 199 | mit | C# | |
Powerful .NET library for benchmarking | ||||||||||
Frameworkbenchmarks | 6,888 | 13 hours ago | 108 | other | Java | |||||
Source for the TechEmpower Framework Benchmarks project | ||||||||||
Web Frameworks | 6,623 | 2 days ago | 13 | April 27, 2021 | 185 | mit | PHP | |||
Which is the fastest web framework? | ||||||||||
Bigcache | 6,404 | 206 | 495 | 12 days ago | 34 | April 04, 2022 | 78 | apache-2.0 | Go | |
Efficient cache for gigabytes of data written in Go. | ||||||||||
Criterion.rs | 3,326 | 245 | 3,126 | a day ago | 23 | September 10, 2022 | 116 | apache-2.0 | Rust | |
Statistics-driven benchmarking library for Rust | ||||||||||
Jquery Dynatable | 2,788 | 4 years ago | 1 | March 31, 2015 | 232 | other | JavaScript | |||
A more-fun, semantic, alternative to datatables | ||||||||||
Tsung | 2,397 | a month ago | 1 | February 27, 2018 | 123 | gpl-2.0 | Erlang | |||
Tsung is a high-performance benchmark framework for various protocols including HTTP, XMPP, LDAP, etc. |
🚂 Summary. The Train Benchmark is a framework for measuring the performance of continuous model transformations, with a particular emphasis on the performance of incremental query reevaluation. The benchmark is actively developed since 2011.
📖 Documentation. If you are interested in implementing the benchmark on your tool, please visit the documentation.
🎥 Presentation. For a short summary, check out this presentation, delivered at the Linked Data Benchmark Council's 9th Technical User Community meeting.
📚 Publications. The definitive publication on the benchmark is our journal paper The Train Benchmark: cross-technology performance evaluation of continuous model queries. For use cases, also check out the related publications.
💻 Technologies. The framework is implemented in Java 8 (for the main components) and Groovy (for scripts). The visualization is handled by R scripts. Both the build and the benchmark process in governed by Gradle.
👋 Contributions welcome. If you would like to implement the benchmark on your tool, we recommend to read the documentation and also please do not hesitate to get in touch!
⚠️ Warning. The Train Benchmark is designed to run in an isolated server environment, e.g. virtual machines in the cloud. Some implementations may shut down or delete existing databases, so only run it on your developer workstation if you understand the consequences. See also issue #75.
⚠️ Warning. The Train Benchmark has a fork for the 2015 Transformation Tool Contest, primarily targeting EMF tools. That fork is no longer maintained. You should use this repository, containing the full, cross-technology Train Benchmark (also supporting RDF, SQL and property graph databases).
📄 Citing the benchmark. For referencing the benchmark, please cite the paper in Software and Systems Modeling with the following BibTeX snippet.
📐 Models. Pre-generated models for scale factors 1 to 4096 are available as a tar.zst
package.
@article{DBLP:journals/sosym/SzarnyasIRV18,
author = {G{\'{a}}bor Sz{\'{a}}rnyas and
Benedek Izs{\'{o}} and
Istv{\'{a}}n R{\'{a}}th and
D{\'{a}}niel Varr{\'{o}}},
title = {The Train Benchmark: cross-technology performance evaluation of continuous
model queries},
journal = {Software and System Modeling},
volume = {17},
number = {4},
pages = {1365--1393},
year = {2018},
url = {https://doi.org/10.1007/s10270-016-0571-8},
doi = {10.1007/s10270-016-0571-8},
timestamp = {Fri, 07 Sep 2018 14:25:47 +0200},
biburl = {https://dblp.org/rec/bib/journals/sosym/SzarnyasIRV18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
The project uses the Eclipse Public License 1.0 and was supported by the MONDO EU FP7 (EU ICT-611125) project. It is primarily maintained by the MTA-BME Lendület Research Group on Cyber-Physical Systems.