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Random Data Generator for arbitrary data types

Hacker News

Random Data Generator for arbitrary data types

Datasino is a command line tool that can come handy when load testing a service or database. Give it a data schema (many compound types supported, including recursive types), an encoding (JSON, CSV or ClickHouse) and a target (a file or a Kafka partition) and a data rate and it will generate a reasonably optimized (native code) random data source. See the top of the README for some examples. If you have any ideas on how to extend this tool so that it's useful to more people, please let me know.

Visit productView on Hacker NewsJan 25, 2022
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5points
9comments
Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide, clickhouse, io · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: coding, code · Missing: mac, agents, macos
43%43% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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