Pinecone · Schema
BackupModel
The BackupModel describes the configuration and status of a Pinecone backup.
Vector DatabasesAIEmbeddingsRAG
Properties
| Name | Type | Description |
|---|---|---|
| backup_id | string | Unique identifier for the backup. |
| source_index_name | string | Name of the index from which the backup was taken. |
| source_index_id | string | ID of the index. |
| name | string | Optional user-defined name for the backup. |
| description | string | Optional description providing context for the backup. |
| status | string | Current status of the backup (e.g., Initializing, Ready, Failed). |
| cloud | string | Cloud provider where the backup is stored. |
| region | string | Cloud region where the backup is stored. |
| dimension | integer | The dimensions of the vectors to be inserted in the index. |
| metric | string | The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the `vector_type` is `de |
| schema | object | |
| record_count | integer | Total number of records in the backup. |
| namespace_count | integer | Number of namespaces in the backup. |
| size_bytes | integer | Size of the backup in bytes. |
| tags | object | |
| created_at | string | Timestamp when the backup was created. |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "#/components/schemas/BackupModel",
"title": "BackupModel",
"description": "The BackupModel describes the configuration and status of a Pinecone backup.",
"type": "object",
"properties": {
"backup_id": {
"example": "670e8400-e29b-41d4-a716-446655440001",
"description": "Unique identifier for the backup.",
"type": "string"
},
"source_index_name": {
"example": "my-index",
"description": "Name of the index from which the backup was taken.",
"type": "string"
},
"source_index_id": {
"example": "670e8400-e29b-41d4-a716-446655440000",
"description": "ID of the index.",
"type": "string"
},
"name": {
"example": "backup-2025-02-04",
"description": "Optional user-defined name for the backup.",
"type": "string"
},
"description": {
"example": "Backup before bulk update.",
"description": "Optional description providing context for the backup.",
"type": "string"
},
"status": {
"example": "Ready",
"description": "Current status of the backup (e.g., Initializing, Ready, Failed).",
"type": "string"
},
"cloud": {
"example": "aws",
"description": "Cloud provider where the backup is stored.",
"type": "string"
},
"region": {
"example": "us-east-1",
"description": "Cloud region where the backup is stored.",
"type": "string"
},
"dimension": {
"example": 1536,
"description": "The dimensions of the vectors to be inserted in the index.",
"type": "integer",
"format": "int32",
"minimum": 1,
"maximum": 20000
},
"metric": {
"description": "The distance metric to be used for similarity search. You can use 'euclidean', 'cosine', or 'dotproduct'. If the 'vector_type' is 'sparse', the metric must be 'dotproduct'. If the `vector_type` is `dense`, the metric defaults to 'cosine'.\nPossible values: `cosine`, `euclidean`, or `dotproduct`.",
"x-enum": [
"cosine",
"euclidean",
"dotproduct"
],
"type": "string"
},
"schema": {
"$ref": "#/components/schemas/MetadataSchema"
},
"record_count": {
"example": 120000,
"description": "Total number of records in the backup.",
"type": "integer"
},
"namespace_count": {
"example": 3,
"description": "Number of namespaces in the backup.",
"type": "integer"
},
"size_bytes": {
"example": 10000000,
"description": "Size of the backup in bytes.",
"type": "integer"
},
"tags": {
"$ref": "#/components/schemas/IndexTags"
},
"created_at": {
"description": "Timestamp when the backup was created.",
"type": "string"
}
},
"required": [
"backup_id",
"source_index_name",
"source_index_id",
"status",
"cloud",
"region"
]
}