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

Crayon
JobsPikr
ReviewTrackers
Revinate
No-code web scrapers on Apify that turn public web data into clean, structured datasets (CSV, JSON, LLM-ready).
Which is more popular?
Based on our record, mlsql seems to be more popular. It has been mentioned 2 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | github.com | factden.com |
| Pricing | — | |
| Company | — | Startup from India · 1 - 9 employees · 2023 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of mlsql yet.
FactDen builds maintained web-scraping tools (Apify Actors) that turn hard-to-reach public data into clean JSON, CSV, or Excel — no proxies, anti-bot tuning, or code required. Every actor ships exact-date fields, booking-link/owner-response layers where relevant, and a markdownContent block ready...
What each product offers, as listed by its team.


No features have been listed yet.
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
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Overall verdict
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How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing mlsql and FactDen.
FactDen's answer:
FactDen actors output dual datasets with clean joins - reviews + per-product summaries, jobs + company profiles - so downstream pipeline work is minimal. Every actor ships with a built-in cost cap, a markdown column for direct LLM/RAG ingestion, and active anti-bot maintenance. The G2 actor extracts switching signals (which competitor a reviewer left and why) - a field most review scrapers skip entirely.
FactDen's answer:
Most alternatives are either monthly-seat data brokers or unmaintained scrapers that break silently. FactDen charges only for what you extract (pay-per-event), ships structured multi-dataset output ready for analytics pipelines, and patches anti-bot changes as target sites update. No contract, no minimum spend.
FactDen's answer:
FactDen's answer:
Built by a scraping engineer who kept running into the same gap - most Apify actors produce flat, single-dataset output with no maintenance when sites update their anti-bot stack. FactDen was started to fill that: production-grade actors with dual-dataset output, cost caps, and ongoing maintenance from day one.
FactDen's answer:
FactDen's answer:
Not yet disclosed
Share your experience with using mlsql and FactDen. For example, how are they different and which one is better?
Recommendations tracked on public social media and blogs since March 2021.


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
I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago
Tracking FactDen since Jun 2026.
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Crayon market and competitive intelligence tools provide insights and inspiration for marketing, sales, and product management.
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