Types and Formats

Measure Types

This section describes the various types that can be assigned to a measure. A measure can only have one type.

`string`

This measure type allows defining measures as a string value.

The sql parameter is required and must include any valid SQL expression with an aggregate function that returns a value of the string type.

In the example below, we create a string measure by converting a numerical value to a string:


cube(`orders`, {
  // ...
 
  measures: {
    high_or_low: {
      type: `string`,
      sql: `CASE WHEN ${CUBE.number} > 100 THEN 'high' ELSE 'low' END`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: high_or_low
        sql: "CASE WHEN {CUBE.number} > 100 THEN 'high' ELSE 'low' END"
        type: string

`time`

This measure type allows defining measures as a time value.

The sql parameter is required and must include any valid SQL expression with an aggregate function that returns a value of the timestamp type.

In the example below, we create a time measure from an existing dimension:


cube(`orders`, {
  // ...
 
  measures: {
    last_order: {
      sql: `MAX(created_at)`,
      type: `time`
    }
  },
 
  dimensions: {
    created_at: {
      sql: `created_at`,
      type: `time`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: last_order
        sql: "MAX(created_at)"
        type: time
 
    dimensions:
      - name: created_at
        sql: created_at
        type: time

`boolean`

The boolean measure type can be used to condense data into a single boolean value.

The sql parameter is required and must include any valid SQL expression with an aggregate function that returns a value of the boolean type.

The example below adds an is_completed measure which only returns true if all orders have the completed status:


cube(`orders`, {
  // ...
 
  measures: {
    is_completed: {
      sql: `BOOL_AND(status = 'completed')`,
      type: `boolean`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: is_completed
        sql: "BOOL_AND(status = 'completed')"
        type: boolean

`number`

The number type is usually used, when performing arithmetic operations on measures, e.g., in calculated measures.

The sql parameter is required and must include any valid SQL expression with an aggregate function that returns a value of the numeric type.


cube(`orders`, {
  // ...
 
  measures: {
    purchases_ratio: {
      sql: `${purchases} / ${count} * 100.0`,
      type: `number`,
      format: `percent`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: purchases_ratio
        sql: "{purchases} / {count} * 100.0"
        type: number
        format: percent

You can put any sql into number measure as long as it’s an aggregate expression:


cube(`orders`, {
  // ...
 
  measures: {
    ratio: {
      sql: `SUM(${CUBE}.amount) / count(*)`,
      type: `number`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: ratio
        sql: "SUM({CUBE}.amount) / count(*)"
        type: number

`number_agg`

The number_agg type is used when you need to write a custom aggregate function in the sql parameter that isn’t covered by standard measure types like sum, avg, min, etc.

The number_agg type is only available in Tesseract, the next-generation data modeling engine . Tesseract is currently in preview. Use the CUBEJS_TESSERACT_SQL_PLANNER environment variable to enable it.

Unlike the number type which is used for calculations on measures (e.g., SUM(revenue) / COUNT(*)), number_agg indicates that the sql parameter contains a direct SQL aggregate function.

The sql parameter is required and must include a custom aggregate function that returns a numeric value.


cube(`orders`, {
  // ...
 
  measures: {
    median_price: {
      sql: `PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY price)`,
      type: `number_agg`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: median_price
        sql: "PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY price)"
        type: number_agg

`count`

Performs a table count, similar to SQL’s COUNT function. However, unlike writing raw SQL, Cube will properly calculate counts even if your query’s joins will produce row multiplication.

You do not need to include the sql parameter for the measure of this type.

drill_members parameter is commonly used with type count. It allows users to click on the measure in the UI and inspect individual records that make up a count. Learn more about Drill Downs.


cube(`orders`, {
  // ...
 
  measures: {
    number_of_users: {
      type: `count`,
      // optional
      drill_members: [id, name, email, company]
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: number_of_users
        type: count
        drill_members:
          - id
          - name
          - email
          - company

`count_distinct`

Calculates the number of distinct values in a given field. It makes use of SQL’s COUNT DISTINCT function.

The sql parameter is required and must include any valid SQL expression of any type (without an aggregate function).


cube(`orders`, {
  // ...
 
  measures: {
    unique_user_count: {
      sql: `user_id`,
      type: `count_distinct`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: unique_user_count
        sql: user_id
        type: count_distinct

`count_distinct_approx`

Calculates approximate number of distinct values in a given field. Unlike count_distinct measure type, count_distinct_approx is decomposable aggregate function or additive. This allows its usage in additive rollup pre-aggregations which are much more versatile than non-additive ones. It uses special SQL backend-dependent functions to estimate distinct counts, usually based on HyperLogLog or similar algorithms. Wherever possible Cube will use multi-stage HLL which significantly improves calculation of distinct counts at scale.

The sql parameter is required and must include any valid SQL expression of any type (without an aggregate function).


cube(`orders`, {
  // ...
 
  measures: {
    unique_user_count: {
      sql: `user_id`,
      type: `count_distinct_approx`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: unique_user_count
        sql: user_id
        type: count_distinct_approx

`sum`

Adds up the values in a given field. It is similar to SQL’s SUM function. However, unlike writing raw SQL, Cube will properly calculate sums even if your query’s joins will result in row duplication.

The sql parameter is required and must include any valid SQL expression of the numeric type (without an aggregate function).


cube(`orders`, {
  // ...
 
  measures: {
    revenue: {
      sql: `amount`,
      type: `sum`
    },
 
    revenue_2: {
      sql: `${charges_amount}`,
      type: `sum`
    },
 
    revenue_3: {
      sql: `fee * 0.1`,
      type: `sum`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: revenue
        sql: amount
        type: sum
 
      - name: revenue_2
        sql: "{charges_amount}"
        type: sum
 
      - name: revenue_3
        sql: fee * 0.1
        type: sum

`avg`

Averages the values in a given field. It is similar to SQL’s AVG function. However, unlike writing raw SQL, Cube will properly calculate averages even if your query’s joins will result in row duplication.

The sql parameter is required and must include any valid SQL expression of the numeric type (without an aggregate function).


cube(`orders`, {
  // ...
 
  measures: {
    avg_transaction: {
      sql: `${transaction_amount}`,
      type: `avg`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: avg_transaction
        sql: "{transaction_amount}"
        type: avg

`min`

Type of measure min is calculated as a minimum of values defined in sql.

The sql parameter is required and must include any valid SQL expression of the numeric type (without an aggregate function).


cube(`orders`, {
  // ...
 
  measures: {
    date_first_purchase: {
      sql: `date_purchase`,
      type: `min`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: date_first_purchase
        sql: date_purchase
        type: min

`max`

Type of measure max is calculated as a maximum of values defined in sql.

The sql parameter is required and must include any valid SQL expression of the numeric type (without an aggregate function).


cube(`orders`, {
  // ...
 
  measures: {
    date_last_purchase: {
      sql: `date_purchase`,
      type: `max`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: date_last_purchase
        sql: date_purchase
        type: max

Measure Formats

When creating a measure you can explicitly define the format you’d like to see as output.

`percent`

percent is used for formatting numbers with a percent symbol.


cube(`orders`, {
  // ...
 
  measures: {
    purchase_conversion: {
      sql: `${purchase} / ${checkout} * 100.0`,
      type: `number`,
      format: `percent`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: purchase_conversion
        sql: "{purchase} / {checkout} * 100.0"
        type: number
        format: percent

`currency`

currency is used for monetary values.


cube(`orders`, {
  // ...
 
  measures: {
    total_amount: {
      sql: `amount`,
      type: `sum`,
      format: `currency`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    measures:
      - name: total_amount
        sql: amount
        type: sum
        format: currency

Dimension Types

This section describes the various types that can be assigned to a dimension. A dimension can only have one type.

`time`

In order to be able to work with time series data, Cube needs to identify a time dimension which is a timestamp column in your database. You can define several time dimensions in a single cube.


cube(`orders`, {
  // ...
 
  dimensions: {
    completed_at: {
      sql: `completed_at`,
      type: `time`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: completed_at
        sql: completed_at
        type: time

Note that the type of the target column should be TIMESTAMP. If your time-based column is type DATE or another temporal type, you should cast it to a timestamp in the sql parameter of the dimension.

Please see this recipe if your datetime information is stored as a string.

`string`

string is typically used with fields that contain letters or special characters.

The sql parameter is required and must include any valid SQL expression with an aggregate function that returns a value of the string type.

The following model creates a field full_name by combining 2 fields: first_name and last_name:


cube(`orders`, {
  // ...
 
  dimensions: {
    full_name: {
      sql: `CONCAT(${first_name}, ' ', ${last_name})`,
      type: `string`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: full_name
        sql: "CONCAT({first_name}, ' ', {last_name})"
        type: string

`number`

number is typically used with fields that contain number or integer.


cube(`orders`, {
  // ...
 
  dimensions: {
    amount: {
      sql: `amount`,
      type: `number`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: amount
        sql: amount
        type: number

`boolean`

boolean is used with fields that contain boolean data or data coercible to boolean. For example:


cube(`orders`, {
  // ...
 
  dimensions: {
    is_enabled: {
      sql: `is_enabled`,
      type: `boolean`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: is_enabled
        sql: is_enabled
        type: boolean

`switch`

switch type is used to define a dimension that can only take one of the predefined set of values. It is similar to an enum type in programming languages. They are particularly useful for defining case measures.

switch dimensions are powered by Tesseract, the next-generation data modeling engine . Tesseract is currently in preview. Use the CUBEJS_TESSERACT_SQL_PLANNER environment variable to enable it.

You do not need to include the sql parameter for the dimension of this type.


cube(`orders`, {
  // ...
 
  dimensions: {
    currency: {
      type: `switch`,
      values: [
        `USD`,
        `EUR`,
        `GBP`
      ]
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: currency
        type: switch
        values:
          - USD
          - EUR
          - GBP

When switch dimensions are queried or introspected using the /v1/meta REST API endpoint, they are represented as dimensions of type string.

`geo`

geo dimension is used to display data on the map. Unlike other dimension types it requires to set two fields: latitude and longitude.


cube(`orders`, {
  // ...
 
  dimensions: {
    location: {
      type: `geo`,
      latitude: {
        sql: `${CUBE}.latitude`
      },
      longitude: {
        sql: `${CUBE}.longitude`
      }
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: location
        type: geo
        latitude:
          sql: "{CUBE}.latitude"
        longitude:
          sql: "{CUBE}.longitude"

Dimension Formats

`imageUrl`

imageUrl is used for displaying images in table visualization. In this case sql parameter should contain full path to the image.


cube(`orders`, {
  // ...
 
  dimensions: {
    image: {
      sql: `CONCAT('https://img.example.com/id/', ${id})`,
      type: `string`,
      format: `imageUrl`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: image
        sql: "CONCAT('https://img.example.com/id/', {id})"
        type: string
        format: imageUrl

`id`

id is used for IDs. It allows to eliminate applying of comma for 5+ digit numbers which is default for type number. The sql parameter is required and can take any valid SQL expression.


cube(`orders`, {
  // ...
 
  dimensions: {
    image: {
      sql: `id`,
      type: `number`,
      format: `id`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: image
        sql: id
        type: number
        format: id

`link`

link is used for creating hyperlinks. link parameter could be either String or Object. Use Object, when you want to give a specific label to link. See examples below for details.

The sql parameter is required and can take any valid SQL expression.


cube(`orders`, {
  // ...
 
  dimensions: {
    order_link: {
      sql: `'http://myswebsite.com/orders/' || id`,
      type: `string`,
      format: `link`
    },
 
    crm_link: {
      sql: `'https://na1.salesforce.com/' || id`,
      type: `string`,
      format: {
        label: `View in Salesforce`,
        type: `link`
      }
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: order_link
        sql: "'http://myswebsite.com/orders/' || id"
        type: string
        format: link
 
      - name: crm_link
        sql: "'https://na1.salesforce.com/' || id"
        type: string
        format:
          label: View in Salesforce
          type: link

`currency`

currency is used for monetary values.


cube(`orders`, {
  // ...
 
  dimensions: {
    amount: {
      sql: `amount`,
      type: `number`,
      format: `currency`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: amount
        sql: amount
        type: number
        format: currency

`percent`

percent is used for formatting numbers with a percent symbol.


cube(`orders`, {
  // ...
 
  dimensions: {
    open_rate: {
      sql: `COALESCE(100.0 * ${uniq_open_count} / NULLIF(${delivered_count}, 0), 0)`,
      type: `number`,
      format: `percent`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: open_rate
        sql:
          "COALESCE(100.0 * {uniq_open_count} / NULLIF({delivered_count}, 0), 0)"
        type: number
        format: percent

Custom time formats

Dimensions with time type support custom formatting using POSIX strftime format strings with d3-time-format extensions.

Custom time formatting is subject to support in visualization tools. Check APIs & Integrations for details.


cube(`orders`, {
  // ...
 
  dimensions: {
    created_at: {
      sql: `created_at`,
      type: `time`,
      format: `%Y-%m-%d %H:%M:%S`
    }
  }
})


cubes:
  - name: orders
    # ...
 
    dimensions:
      - name: created_at
        sql: created_at
        type: time
        format: "%Y-%m-%d %H:%M:%S"

Common format examples

Format string	Example output
`%m/%d/%Y %H:%M`	12/04/2025 14:30
`%Y-%m-%d %H:%M:%S`	2025-12-04 14:30:00
`%B %d, %Y`	December 04, 2025
`%b %d, %Y`	Dec 04, 2025
`%I:%M %p`	02:30 PM
`%A, %B %d`	Thursday, December 04
`Q%q %Y`	Q4 2025
`Week %V, %Y`	Week 49, 2025

Supported format specifiers

Specifier	Description
`%a`	Abbreviated weekday name
`%A`	Full weekday name
`%b`	Abbreviated month name
`%B`	Full month name
`%c`	Locale’s date and time
`%d`	Day of month [01,31]
`%e`	Space-padded day of month
`%f`	Microseconds
`%g`	ISO 8601 year without century
`%G`	ISO 8601 year with century
`%H`	Hour (24-hour) [00,23]
`%I`	Hour (12-hour) [01,12]
`%j`	Day of year [001,366]
`%L`	Milliseconds
`%m`	Month [01,12]
`%M`	Minute [00,59]
`%p`	AM or PM
`%q`	Quarter [1,4]
`%Q`	Milliseconds since UNIX epoch
`%s`	Seconds since UNIX epoch
`%S`	Second [00,61]
`%u`	Monday-based weekday [1,7]
`%U`	Sunday-based week number [00,53]
`%V`	ISO 8601 week number
`%w`	Sunday-based weekday [0,6]
`%W`	Monday-based week number [00,53]
`%x`	Locale’s date
`%X`	Locale’s time
`%y`	Year without century [00,99]
`%Y`	Year with century
`%Z`	Time zone name
`%%`	Literal percent sign

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