Schemas

Schemas are how you define what your mock data should look like. They are defined as JSON Objects, with each key representing a field in the data.

Each top-level key is the name of the field, in database terms, this would be your column name. Each key is an object, beneath which, you must define a type field. The value of the type field must be one of the supported Data Types. Some Data Type require parameters, which are supplied with a params key at the same level as the type key. The params key is also an object, beneath which you must supply the key-value pairs as required by the type.

It’s very simple, but it can be easier to understand with an example. This is a valid Mockingbird schema:

{
  "some_int": {
    "type": "mockingbird.int"
  },
  "some_values": {
    "type": "mockingbird.pick",
    "params": [
      {
        "values": [
          123,
          456
        ]
      }
    ]
  }
}

The first object in our schema is some_int, which has the type int. The second object is some_values, which has the type values, and has additional parameters specified inside the params object.

The output of this schema would look like:

{
    "some_int": 100,
    "some_values": 123
}

Arrays

All types can be generated as arrays. Simply add a count key at the same level as the type key.

{
  "some_int": {
    "type": "mockingbird.int",
    "count": 3
  }
}

Preset Schemas

You can write your own custom schema, or use any of the preset schemas.

You can find the definitions of all preset Schemas here.

Contributions for more preset schemas are welcome!

Simple Example

The Simple Example schema is a basic default schema to get you started.

eCommerce Transactions

The eCommerce Transactions schema is an example of e-commerce style sales data.

Stock Prices

The Stock Prices schema is an example of a stock ticker data feed.

Flight Bookings

The Flight Bookings schema is an example of a travel agent-style data feed.

Content Tracking

The Content Tracking schema is an example of an event tracking data feed.

Web Analytics Starter Kit

The Web Analytics Starter Kit allows you to generate mock data for the Tinybird Web Analytics Starter Kit.

Log Analytics Starter Kit

The Log Analytics Starter Kit allows you to generate mock data for the Tinybird Log Analytics Starter Kit.

Flappybird

The Flappybird schema is an example of a stream of game events.

Sportsbetting

The Sportsbetting schema is an example of a stream of Sportsbetting location events.