Skip to content

Latest commit

 

History

History
142 lines (106 loc) · 5.14 KB

README.md

File metadata and controls

142 lines (106 loc) · 5.14 KB
Raw

TSPERF Time Series Database Benchmark Suite

TSPERF is a tool for evaluating and comparing the performance of time series databases, in the spirit of TimescaleDB's Time Series Benchmark Suite (TSBS).

» Documentation | Changelog | PyPI | Issues | Source code | License

CI Coverage Status License Downloads per month

Supported Python versions Status Package version

About

The tsperf program includes both a database workload generator, and a query timer. That effectively spans two domains, one for writing data, and another one for reading.

  • Data Generator: Generate time series data and feed it into database. Use tsperf write --help to explore its options.
  • Query Timer: Probe responsiveness of database on the read path. Use tsperf read --help to explore its options.

For the purpose of capacity testing, both domains try to simulate the generation and querying of time-series data. As the program is easy to use, it provides instant reward without the need to set up a whole data ingestion chain.

Features

General

  • Generate random data which follows a statistical model to better reflect real world scenarios, real world data is almost never truly random.
  • The "steady load"-mode can simulate a constant load of a defined number of messages per second.
  • Ready-made to deploy and scale data generators with Docker containers. In order to maximize performance, multiple instances of the data generator can be run in parallel. This can be achieved by parallelizing using Kubernetes.
  • Metrics are exposed for consumption by Prometheus.

Data Generator

  • Capability to define your own schema.
  • Full control on how many values will be inserted.
  • Scale out to multiple clients is a core concept.
  • Huge sets of data can be inserted without creating files as intermediate storage.

Database Coverage

  • CrateDB
  • InfluxDB
  • Microsoft SQL Server
  • MongoDB
  • PostgreSQL
  • TimescaleDB
  • Timestream

Install

Python package

pip install --user tsperf

Docker image

alias tsperf="docker run -it --rm --network=host ghcr.io/crate/tsperf:latest tsperf"
tsperf --help

Usage

Please refer to the usage documentation.

Prior Art

cr8 + mkjson

mkjson combined with cr8 insert-json makes it easy to generate random entries into a table. See generate data sets using mkjson for an example how to use cr8 together with mkjson.

TSBS

The Time Series Benchmark Suite (TSBS) is a collection of Go programs that are used to generate datasets and then benchmark read and write performance of various databases.

Project Information

Contributing

We are always happy to receive code contributions, ideas, suggestions and problem reports from the community.

So, if you’d like to contribute you’re most welcome. Spend some time taking a look around, locate a bug, design issue or spelling mistake and then send us a pull request or open an issue on GitHub.

Thanks in advance for your efforts, we really appreciate any help or feedback.

Acknowledgements

Thanks to all the contributors who helped to co-create and conceive tsperf in one way or another and kudos to all authors of the foundational libraries.

License

This project is licensed under the terms of the Apache 2.0 license.