Insert a document (HTTP)

Inserts a single document into a collection.

Documents are stored in collections. They represent a single row or record of data in Hyper-Converged Database (HCD) databases. For more information, see About collections with the Data API (HTTP).

If the collection is vector-enabled, pregenerated vector embeddings can be included by using the reserved $vector field. You can later use the $vector field to perform a vector search.

Ready to write code? See the examples for this method to get started.

Result

Inserts the specified document and returns a JSON object that includes the ID of the inserted document.

The ID value depends on the ID type. For more information, see Document IDs (HTTP).

Example response:

{
  "status": {
    "insertedIds": [
      "3f557bef-fd53-47ea-957b-effd53c7eaec"
    ]
  }
}

Signature

Use the insertOne command.

curl -sS -L -X POST "API_ENDPOINT/api/json/v1/KEYSPACE_NAME/COLLECTION_NAME" \
--header "Token: APPLICATION_TOKEN" \
--header "Content-Type: application/json" \
--data '{
  "insertOne": {
    "document": DOCUMENT_JSON_OBJECT
  }
}'

Parameters

Name Type Summary

document

object

A JSON object describing the document to insert.

A document can contain user-defined and reserved fields.

User-defined field names can be any non-empty sequence of Unicode characters, with the following exceptions:

  • Field names cannot start with $.

  • Field names cannot be exactly *.

  • If a field name includes & or ., you must escape those characters when you use the field in a filter, sort, projection, or update. For more information, see Work with . and & in field names (HTTP).

Reserved fields are tied to specific functionality. Include the following reserved fields in your documents, if applicable:

  • _id: An optional unique identifier for the document. If _id is omitted, it is created automatically based on the collection’s ID type. For more information, see Document IDs (HTTP).

  • $vector: An optional array of numbers representing a vector embedding for vector search. The $vector field is only supported for vector-enabled collections.

For examples, see Examples.

Examples

The following examples demonstrate how to insert a document into a collection.

Insert a document

curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "title": "Hidden Shadows of the Past",
      "genres": ["Biography", "Graphic Novel", "Dystopian", "Drama"],
      "metadata": {
          "isbn": "978-1-905585-40-3",
          "language": "French",
          "edition": "Anniversary Edition"
      },
      "number_of_pages": 245
    }
  }
}'

Insert a document with vector embeddings

Use the reserved $vector field to insert a document with pregenerated vector embeddings.

You can later use this field to perform a vector search.

All embeddings in the collection should use the same provider, model, and dimensions. Mismatched embeddings can cause inaccurate vector searches.

The $vector field is only supported for vector-enabled collections. For more information, see Create a collection that can store vector embeddings and $vector in collections (HTTP).

You can provide the vector embeddings as an array of floats, or you can use $binary to provide the vector embeddings as a Base64-encoded string. $binary can be more performant.

For more information about how to convert an array of floats to a Base64-encoded string, see Binary encoding of vector embeddings.

Array of floats
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "name": "Jane Doe",
      "$vector": [0.08, -0.62, 0.39]
    }
  }
}'
$binary
curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "name": "Jane Doe",
      "$vector": {"$binary": "PaPXCr8euFI+x64U"}
    }
  }
}'

Insert a document and specify the ID

You can specify the _id field directly, or you can use the objectId, uuid, uuidv6, or uuidv7 types.

Example specifying an integer:

curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "name": "Jane Doe",
      "_id": 1
    }
  }
}'

Example using the objectId type:

curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "name": "Jane Doe",
      "_id": { "$objectId": "6672e1cbd7fabb4e5493916f" }
    }
  }
}'

Insert a document with a binary field

You can insert binary data as a Base64-encoded string with $binary.

curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "exampleBinary": {"$binary": "PaPXCr8euFI+x64U"}
    }
  }
}'

Insert a document with nested fields

Although you can use dot notation in a filter to find a document, you cannot use dot notation to insert a document. To specify nested fields in the inserted document, you must build a map, list, or set.

curl -sS -L -X POST "API_ENDPOINT/v1/KEYSPACE_NAME/COLLECTION_NAME" \
  --header "Token: APPLICATION_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{
  "insertOne": {
    "document": {
      "title": "Hidden Shadows of the Past",
      "genres": ["Biography", "Graphic Novel", "Dystopian", "Drama"],
      "metadata": {
        "isbn": "978-1-905585-40-3",
        "language": "French",
        "edition": "Anniversary Edition"
      }
    }
  }
}'

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