Nao1215/sqluv – simple terminal UI for RDBMS and local CSV/TSV/LTSV

Hacker News

Hello HN, I have created a terminal-based client for opening RDBMS and local files. Currently, it supports only basic features, but it should function as a viewer. - Supports MySQL, PostgreSQL, SQLite3, and SQL Server as RDBMS. - Supports CSV, TSV, and LTSV as local files. - Executes SQL queries and displays results (with some query execution limitations) - SQL query history. - Saves RDBMS connection information. - Provides over 10 color schemes If many people are interested in this tool, I plan to continue its development! Happy hacking!

Visit product View on Hacker NewsMar 21, 2025

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3points

5comments

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, created · Missing: reddit linkedin, podcasting, latex

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos

38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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