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mlsql VS Subti.app

Compare mlsql VS Subti.app and see what are their differences

mlsql

Infer SQL queries from plain-text questions and table headers.

Rating
0 reviews
Alternatives Is it good?
Subti.app

Learn languages from films in VLC with clickable subtitles, contextual translations, vocabulary review, and Anki export.

Rating
0 reviews
Pricing
Freemium $9.99 / One-off (One-time purchase, one person, up to 2 Macs)
Alternatives Is it good?
warmup.rocks
warmup.rocks keeps your CDN cache warm in every edge location worldwide: Cloudflare, Fastly, Akamai, CloudFront and more. Warming from 42 countries, hit-ratio analytics. sponsored

Which is more popular?

Based on our record, mlsql seems to be more popular. It has been mentioned 2 times since March 2021.

social mentions
2 vs 0
LMS popularity
100% vs 0%
alternatives listed
1 vs 7

Base details

Website, pricing, platforms and company facts side by side.

mlsql
Subti.app
Website github.com subti.app
Pricing —
Freemium $9.99 / One-off (One-time purchase, one person, up to 2 Macs) Official pricing
Platforms —
MacOS Mac Mac OSX
Company — Startup from Georgia · 1 - 9 employees · 2026
Listed in
Education LMS Online Learning Web App +1
Language Learning Language Translation Education Spaced Repetition Studying Translation Subtitles +4

About mlsql and Subti.app

In their own words, as submitted to SaaSHub.

mlsql
Subti.app

No description of mlsql yet.

Subti is a macOS companion for learning languages from films and TV shows in VLC. Click subtitle words or select phrases to get contextual translations, save useful vocabulary, review it with spaced repetition, and export it to Anki. Subti is local-first, requires no account, and supports local...

Read more about Subti.app

Features and specs

What each product offers, as listed by its team.

mlsql 0 features
Subti.app 8 features

No features have been listed yet.

  • Clickable Subtitles
    Option-click words or select phrases directly from VLC subtitles
  • Contextual Translation
    Translates words and expressions using the surrounding subtitle context
  • Vocabulary Review
    History, personal Dictionary, and spaced repetition review
  • Anki export
    Export saved vocabulary to Anki with context
  • Local-first
    Supports local translation backends and requires no account
  • VLC integration
    Works as a macOS companion overlay for VLC 3.0+
  • Privacy
    No behavioral telemetry
  • System Requirements
    macOS 14+

Analysis

An editorial look at what each product does well and who it suits.

mlsql
Subti.app

Overall verdict

  • MLSQL is a solid open-source unified platform that blends SQL with machine learning, making data engineering and ML workflows accessible through a single, declarative language. It's a good choice for teams looking to streamline big data and ML pipelines without switching between multiple tools.

Why this product is good

  • It unifies data processing and machine learning under a single SQL-like syntax, lowering the learning curve for data teams.
  • Built on top of Apache Spark, it leverages a proven distributed computing engine for handling large-scale data.
  • Open-source and actively developed, allowing customization and community-driven improvements.
  • Supports the full ML lifecycle including data preprocessing, training, and deployment within one workflow.
  • Reduces the need to context-switch between separate ETL, analytics, and ML tools.

Recommended for

  • Data engineers and data scientists who prefer SQL-centric workflows
  • Teams working with big data on Apache Spark
  • Organizations wanting to unify ETL and machine learning pipelines
  • Companies seeking an open-source alternative to fragmented ML tooling
  • Analysts looking to build ML models without deep programming expertise

No analysis of Subti.app yet.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
mlsql
Subti.app
100% 100%
LMS
0% 0%
0% 0%
Language Translation
100% 100%
50% 50%
Education
50% 50%
100% 100%
Online Learning
0% 0%

Questions & Answers

As answered by people managing mlsql and Subti.app.

What makes your product unique?

Subti.app's answer:

Subti makes VLC subtitles interactive on macOS. You can click individual words or select whole phrases, get contextual translations without leaving the film, save useful vocabulary, review it with spaced repetition, and export it to Anki. It is local-first, requires no account, and can work with local translation models

Why should a person choose your product over its competitors?

Subti.app's answer:

Subti is focused on a simple workflow: watch, click, understand, save, and review. It works directly with VLC and local video files instead of requiring a browser-based streaming service. It also supports phrase-level contextual translation, local translation backends, spaced repetition, and Anki export in one macOS app

How would you describe the primary audience of your product?

Subti.app's answer:

Language learners who watch films and TV shows with subtitles, especially intermediate and advanced learners who want to learn vocabulary and expressions from real dialogue without constantly switching between the video player, translator, notes, and flashcard apps

What's the story behind your product?

Subti.app's answer:

Subti started from a personal frustration with learning languages through films. Looking up an unfamiliar word usually meant pausing VLC, opening a translator, copying the subtitle, saving the word somewhere, and then returning to the film. Subti was built to keep that entire workflow inside the viewing experience

Which are the primary technologies used for building your product?

Subti.app's answer:

Subti is a native macOS application built in Swift. It integrates with VLC through a transparent interactive overlay and supports local language models and Ollama for translation. The web and licensing infrastructure uses Cloudflare Workers, D1, R2, Paddle, and Sparkle for updates

User comments

Share your experience with using mlsql and Subti.app. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

mlsql 2 mentions
Subti.app 0 mentions
  • Download the files from Docker Container and locally edit them
    I am working on a project that requires me to take user input (as English) and return SQL queries. We will eventually be working with multiple datasets, which is why the valuenet over at https://github.com/paulfitz/mlsql ended up being... Source: over 4 years ago
  • Clone and edit Docker Projects hosted on Github
    I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago

Tracking Subti.app since Sep 2026.

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