Mock Data FAQs

Question 1

How fast can Mock Data generate records?

Accepted Answer

It's blazing fast, capable of generating 1000 records in approximately 9 milliseconds. This performance is achieved through batch pre-load optimization, where all necessary SQLite seed data is loaded into memory upfront.

Question 2

How does Mock Data handle complex or unique data fields?

Accepted Answer

For complex or highly specific data fields, Mock Data offers an `ai` field type that integrates with Google Gemini AI. You can provide a prompt, and Gemini will generate contextually relevant content, such as product categories.

Question 3

What kind of Taiwan-specific data can it generate?

Accepted Answer

Mock Data excels in Taiwan locales, generating realistic names, phone numbers, ID numbers (with checksum), addresses, counties, and districts. It utilizes comprehensive SQLite seed data for accuracy.

Question 4

What's the process for defining the data structure?

Accepted Answer

You define your desired mock data structure using a simple JSON schema. This schema allows you to specify field names and their types (e.g., number, date, string, boolean, name, address, uuid, ai), including parameters like min/max values or AI prompts, for structured and customized output.

Question 5

What is Mock Data and what are its core capabilities?

Accepted Answer

Mock Data is an ultra-fast, schema-driven tool designed to generate realistic mock data for development and testing. It specializes in creating Taiwan locale-specific data and leverages Gemini AI as a fallback for complex field types.

Mock Data

Mock Data

Key Features

Use Cases

Key Features

Use Cases