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Revise $objectToArray documentation details
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‎articles/cosmos-db/mongodb/vcore/operators/object-expression/$objectToArray.md‎

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---
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title: $objectToArray
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titleSuffix: Overview of the $objectToArray expression in Azure Cosmos DB for MongoDB (vCore)
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titleSuffix: Overview of the $objectToArray operator in Azure Cosmos DB for MongoDB (vCore)
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description: The objectToArray command is used to transform a document (object) into an array of key-value pairs.
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author: avijitgupta
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ms.author: avijitgupta
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ms.service: azure-cosmos-db
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ms.subservice: mongodb-vcore
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ms.topic: language-reference
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ms.date: 08/03/2025
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ms.date: 09/04/2025
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---
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# $objectToArray
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## Syntax
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```javascript
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{ $objectToArray: <object> }
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{
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$objectToArray: <object>
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}
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```
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## Parameters
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## Examples
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Given a sample JSON document representing a store, we can use the `$objectToArray` operator to transform various parts of this document.
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Consider this sample document from the stores collection.
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```json
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{
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"_id": "0fcc0bf0-ed18-4ab8-b558-9848e18058f4",
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"name": "First Up Consultants | Beverage Shop - Satterfieldmouth",
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"location": {
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"lat": -89.2384,
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"lon": -46.4012
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},
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"staff": {
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"totalStaff": {
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"fullTime": 8,
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"partTime": 20
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}
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},
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"sales": {
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"totalSales": 75670,
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"salesByCategory": [
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{
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"categoryName": "Wine Accessories",
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"totalSales": 34440
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},
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{
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"categoryName": "Bitters",
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"totalSales": 39496
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},
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{
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"categoryName": "Rum",
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"totalSales": 1734
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}
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]
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},
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"promotionEvents": [
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{
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"eventName": "Unbeatable Bargain Bash",
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"promotionalDates": {
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"startDate": {
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"Year": 2024,
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"Month": 6,
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"Day": 23
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},
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"endDate": {
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"Year": 2024,
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"Month": 7,
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"Day": 2
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}
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},
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"discounts": [
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{
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"categoryName": "Whiskey",
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"discountPercentage": 7
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},
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{
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"categoryName": "Bitters",
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"discountPercentage": 15
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},
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{
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"categoryName": "Brandy",
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"discountPercentage": 8
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},
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{
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"categoryName": "Sports Drinks",
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"discountPercentage": 22
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},
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{
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"categoryName": "Vodka",
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"discountPercentage": 19
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}
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]
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},
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{
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"eventName": "Steal of a Deal Days",
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"promotionalDates": {
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"startDate": {
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"Year": 2024,
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"Month": 9,
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"Day": 21
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},
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"endDate": {
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"Year": 2024,
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"Month": 9,
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"Day": 29
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}
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},
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"discounts": [
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{
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"categoryName": "Organic Wine",
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"discountPercentage": 19
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},
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{
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"categoryName": "White Wine",
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"discountPercentage": 20
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},
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{
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"categoryName": "Sparkling Wine",
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"discountPercentage": 19
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},
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{
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"categoryName": "Whiskey",
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"discountPercentage": 17
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},
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{
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"categoryName": "Vodka",
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"discountPercentage": 23
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}
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]
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}
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]
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}
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```
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### Example 1: Transforming the `location` object
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The example aggregation pipeline transforms the `location` object into an array of key-value pairs.
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This query transforms the `location` object into an array of key-value pairs.
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```javascript
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db.stores.aggregate([
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])
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```
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The output represents the result of using the `$objectToArray` aggregation operator on the `location` field for each document.
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The first two results returned by this query are:
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```json
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[
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{
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"_id": "a715ab0f-4c6e-4e9d-a812-f2fab11ce0b6",
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"locationArray": [
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}
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]
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}
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]
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```
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### Example 2: Transforming the `salesByCategory` array
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If you want to transform the `salesByCategory` array, you would first need to unwind the array and then apply the `$objectToArray` operator.
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To transform the `salesByCategory` array, first unwind the array and then apply the `$objectToArray` operator.
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```javascript
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db.stores.aggregate([
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])
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```
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Converting subdocuments to key-value pairs is often used when you want to dynamically process field names, especially when:
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- Building generic pipelines.
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- Mapping field names into key-value structures for flexible transformations or further processing.
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The first two results returned by this query are:
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```json
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[
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]
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```
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Converting subdocuments to key-value pairs is often used when you want to dynamically process field names, especially when:
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- Building generic pipelines.
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- Mapping field names into key-value structures for flexible transformations or further processing.
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## Related content
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[!INCLUDE[Related content](../includes/related-content.md)]

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