Mockaroo
Random Data Monster
Universal Data Generator
Dummy File Generator
DUMMY DATABASE
RANDOM.ORG
Wheel of Names
Data generator that can create a table filled with pseudo-random content.

ExpressJS
Koa.js
Backbone.js
Meteor
Sails.js
Famous Engine
AngularJS
Wow your users. Build incredible real-time applications in record time.
Which is more popular?
Based on our record, FeathersJS seems to be more popular. It has been mentioned 39 times since March 2021.
Website, pricing, platforms and company facts side by side.
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DC
Data Creator
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| Website | ecleti.com | feathersjs.com |
| Pricing | — | |
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What each product offers, as listed by its team.

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OSS 2019: FeathersJS with David Lueke
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Recommendations tracked on public social media and blogs since March 2021.

Tracking Data Creator since Mar 2021.
This is just using sqlite under the hood and none of this will scale. Why build your own query builder as well when you could just hook in one of the many ORMs in the NPM ecosystem and add support for 50+ other databases. This also isn't... - Source: Hacker News / over 2 years ago
For backend this might help https://feathersjs.com. I’m not affiliated with them, just a happy user. - Source: Hacker News / over 2 years ago
Feathers.js is a web framework built on top of Express which provides a simple way to develop a scalable and reliable application. Feathers.js supports many databases and works with any frontend technology including iOS, Android, and... - Source: dev.to / almost 3 years ago
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A realistic data generator to test your app
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Sinatra inspired web development framework for node.js -- insanely fast, flexible, and simple
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Random Data Monster is a comprehensive suite of advanced random data generation that features generating secure passwords, names, numbers and more than 30+ Google Sheets custom functions to generate random data.
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Generate realistic Salesforce test data with proper relationships and record types in minutes! Direct upload to sandboxes—no CSV wrangling, no production data risks.
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Give your JS App some Backbone with Models, Views, Collections, and Events
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