starrocks/tpcds-kit — explained in plain English
Analysis updated 2026-07-19 · repo last pushed 2025-01-02
Generate a simulated 10-terabyte retail dataset to stress-test your database.
Run 99 standardized business queries against your data to measure response times.
Benchmark an analytics platform to prove it can handle heavy real-world workloads.
| starrocks/tpcds-kit | abrown/aom | adroxz1122/injected-host-enumeration | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | C | C | C |
| Last pushed | 2025-01-02 | 2020-03-11 | — |
| Maintenance | Stale | Dormant | — |
| Setup difficulty | hard | hard | moderate |
| Complexity | 4/5 | 5/5 | 3/5 |
| Audience | ops devops | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires compiling C source code on Linux or macOS, and generating data at massive scale can require significant disk space and processing time.
The tpcds-kit is a toolkit for generating large sets of fake retail sales data and the complex questions (queries) you would ask about that data. It is based on an industry standard benchmark called TPC-DS, which simulates a realistic retail business with sales, customers, stores, and websites. The project lets teams create test data at a massive scale, for example, 10 terabytes, and then generate 99 different business questions to run against that data to see how fast their system can answer them. This particular fork of the toolkit was adapted specifically for StarRocks, a database system. The original benchmark tools generate queries using standard SQL, but every database has its own quirks and preferred syntax. The project's creators modified the query templates so they work correctly with StarRocks, fixing things like date calculations and adding required naming aliases. The tools themselves are written in C and need to be compiled on your machine, with the README providing instructions for Linux and macOS. Database engineers and performance testers are the main users of this project. If a company is building an analytics platform and wants to prove it can handle heavy workloads, they would use this toolkit to generate a simulated 10-terabyte retail dataset, load it into their database, and then run the 99 generated queries to measure response times. It provides a standardized way to answer the question: "Can our database handle real-world scale?" The project itself is a modified version of an open-source benchmarking kit, with specific adjustments to make the generated SQL compatible with StarRocks' dialect. Beyond the StarRocks-specific changes, the fork also includes fixes from other community contributors that make the toolkit compile on macOS and correct bugs in some of the original query templates.
A toolkit for generating massive fake retail datasets and 99 standard business queries to benchmark database performance. This version is tweaked specifically for the StarRocks database.
Mainly C. The stack also includes C, SQL, StarRocks.
Stale — no commits in 1-2 years (last push 2025-01-02).
This is a modified fork of the open-source TPC-DS benchmark toolkit, the license terms of the original toolkit apply.
Setup difficulty is rated hard, with roughly 1h+ to a first successful run.
Mainly ops devops.
This repo across BitVibe Labs
double-check against the repo, no cap.