Software Alternatives & Startups
Register | Login

Smell Dating VS mlsql

Compare Smell Dating VS mlsql and see what are their differences

SD
Smell Dating

The first mail odor dating service

Rating
0 reviews
Promote on VibeVoted
Alternatives Is it good?
mlsql

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

Rating
0 reviews
Promote on VibeVoted
Alternatives Is it good?
HIVLY.APP
Give Hivly an idea. Get a finished social post. Add a photo and one sentence. Hivly writes the caption, designs the post, and schedules it for Facebook, Instagram, and LinkedIn. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

mlsql might be a bit more popular than Smell Dating. We know about 2 links to it since March 2021 and only 2 links to Smell Dating.

social mentions
2 vs 2
Dating popularity
100% vs 0%
alternatives listed
49 vs 1

Base details

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

SD
Smell Dating
mlsql
Website smell.dating github.com
Listed in
Dating Social Networks Marketing iPhone +1
Education LMS Online Learning Web App +1

Features and specs

What each product offers, as listed by its team.

SD
Smell Dating 4 features
mlsql 0 features
  • Unique Matching Method
    Smell Dating uses natural body scent to match individuals, offering a unique and scientifically-backed method that goes beyond superficial online profiles.
  • Biological Compatibility
    By focusing on scent, Smell Dating potentially matches individuals based on biological and pheromonal compatibility, which could lead to more successful relationships.
  • Novelty and Curiosity
    The unusual concept of smell-based dating piques curiosity and attracts those looking for something different from traditional dating platforms.
  • Detachment from Physical Appearance
    Smell Dating prioritizes olfactory senses over visual cues, encouraging users to focus less on physical appearance and more on chemical attraction.

Possible disadvantages

  • Limited User Base
    As a niche dating service, Smell Dating may have a smaller pool of participants compared to mainstream dating apps, limiting the number of potential matches.
  • Unconventional Approach
    The concept may not appeal to everyone, as it requires users to be open to an unconventional and less common method of finding partners.
  • Hygiene Concerns
    The process of exchanging odor samples can raise hygiene issues or discomfort for some participants, making it less appealing.
  • Lack of Immediate Interaction
    The time taken to collect, send, and process smells might delay initial interactions, unlike digital matches which happen instantly.

No features have been listed yet.

Analysis

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

SD
Smell Dating
mlsql

No analysis of Smell Dating yet.

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

Videos

Walkthroughs and reviews on video.

SD
Smell Dating 1 video + Add
mlsql 0 videos + Add

WHOOPI ATTACKS Ben Carson, SMELL DATING, GOLDEN GIRL sued... || My 2 Cents #2

No mlsql videos yet. You could help us improve this page by suggesting one.

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
SD
Smell Dating
mlsql
100% 100%
Dating
0% 0%
0% 0%
Web App
100% 100%
100% 100%
Social Networks
0% 0%
0% 0%
LMS
100% 100%

User comments

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

Log in or Post with

Social recommendations and mentions

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

SD
Smell Dating 2 mentions
mlsql 2 mentions
  • Ask HN: Why are dating apps so bad? Why hasn't anyone made a good one?
    Random thoughts: - are there any measurable factors indicating someone is a good match? Okcupid claimed to match people with others who gave similar answers to their questions, but I had some fates with a high match % and still no... - Source: Hacker News / over 1 year ago
  • Smell You Later: The Weird Science of How Sweat Attracts
    Reminds me of: https://smell.dating/. - Source: Hacker News / over 5 years ago
  • 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

Alternatives to Smell Dating and mlsql

When comparing Smell Dating and mlsql, you can also consider the following products.

Loading...