head to head · open source

HeidiSQL vs learn-agentic-ai

HeidiSQL has 6,274 GitHub stars, 587 forks, 324 open issues and last shipped 2 days ago. learn-agentic-ai has 4,375 stars, 1,010 forks, 59 open issues and last shipped 11 months ago. HeidiSQL leads on adoption by 43% (6,274 vs 4,375 stars). HeidiSQL is written in Pascal under GPL-2.0; learn-agentic-ai is written in Jupyter Notebook under MIT. HeidiSQL has attracted 9% as many forks as stars, learn-agentic-ai 23%. HeidiSQL was the more recently maintained of the two, and both are self-hostable with no licence fee.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

HeidiSQL ★ 6.3K learn-agentic-ai ★ 4.4K category Infrastructure & Operations

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Side by side

HeidiSQL learn-agentic-ai
GitHub stars ★ 6.3K ★ 4.4K
License GPL-2.0 MIT
Written in Pascal Jupyter Notebook
Last push 2026-09-18 2025-10-26
Forks ⑂ 587 ⑂ 1.0K
Self-hosting Yes Yes
Data ownership Your server Your server

pick HeidiSQL if

  • You weight community size — 6.3K stars and counting
  • You want the GPL-2.0 license terms
  • Your stack matches Pascal
  • You value the larger contributor base for long-term maintenance

full HeidiSQL profile →

pick learn-agentic-ai if

  • You want the learn-agentic-ai feature set and don't need the biggest community
  • You prefer the MIT license terms
  • Your stack matches Jupyter Notebook
  • You evaluated both and learn-agentic-ai fits your workflow better

full learn-agentic-ai profile →

About HeidiSQL

HeidiSQL is a free, GPL 2.0 licensed graphical client for managing MariaDB, MySQL, Microsoft SQL Server, PostgreSQL, SQLite, Interbase and Firebird databases, aimed at developers and database administrators who need to browse, edit and export data without working from a command line.

read the full HeidiSQL overview →

About learn-agentic-ai

learn agentic ai is an MIT licensed Jupyter Notebook learning repository from Panaversity that teaches developers how to design and scale agentic AI systems using the Dapr Agentic Cloud Ascent (DACA) design pattern and agent native cloud technologies.

read the full learn-agentic-ai overview →

More in Infrastructure & Operations

kubernetes ★ 128K Immich ★ 115K frp ★ 110K Uptime Kuma ★ 92K worldmonitor ★ 87K mall ★ 85K

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More Databases projects

Compare either of these against the rest of the Databases field.

HeidiSQL vs mall HeidiSQL vs Prometheus HeidiSQL vs NocoDB HeidiSQL vs etcd HeidiSQL vs DBeaver HeidiSQL vs orm HeidiSQL vs Milvus HeidiSQL vs TiDB HeidiSQL vs drawDB HeidiSQL vs typeorm HeidiSQL vs AnotherRedisDesktopManager HeidiSQL vs Qdrant

Frequently asked questions

Is HeidiSQL or learn-agentic-ai more popular?

HeidiSQL has 6,274 GitHub stars and learn-agentic-ai has 4,375. HeidiSQL has the larger community by that measure.

Are HeidiSQL and learn-agentic-ai free?

Both are open source. HeidiSQL is licensed under GPL-2.0 and learn-agentic-ai under MIT. Neither carries a licence fee.

What is the difference between HeidiSQL and learn-agentic-ai?

HeidiSQL is written in Pascal and learn-agentic-ai in Jupyter Notebook. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, HeidiSQL or learn-agentic-ai?

Choose HeidiSQL if you want the larger community (6,274 stars) or its GPL-2.0 licence terms. Choose learn-agentic-ai if its feature set, stack or MIT licence fits better. Both are self-hostable.