Back up a pod-based index

Customers who sign up for a Standard or Enterprise plan on or after August 18, 2025 cannot create pod-based indexes. Instead, create serverless indexes, and consider using dedicated read nodes for large workloads (millions of records or more, and moderate or high query rates).

This page describes how to create a static copy of a pod-based index, also known as a collection.

Create a collection

To create a backup of your pod-based index, use the create_collection operation.

The following example creates a collection named example-collection from an index named docs-example:

Python

# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="API_KEY")
pc.create_collection("example-collection", "docs-example")

You can create a collection using the Pinecone console.

Check the status of a collection

To retrieve the status of the process creating a collection and the size of the collection, use the describe_collection operation. Specify the name of the collection to check. You can only call describe_collection on a collection in the current project.

The describe_collection operation returns an object containing key-value pairs representing the name of the collection, the size in bytes, and the creation status of the collection.

The following example gets the creation status and size of a collection named example-collection.

Python

# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key='API_KEY')
pc.describe_collection(name="example-collection")

You can check the status of a collection using the Pinecone console.

List your collections

To get a list of the collections in the current project, use the list_collections operation.

Python

from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key='API_KEY')
pc.list_collections()

You can view a list of your collections using the Pinecone console.

Delete a collection

To delete a collection, use the delete_collection operation. Specify the name of the collection to delete.

Deleting the collection takes several minutes. During this time, the describe_collection operation returns the status “deleting”.

Python

# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key='API_KEY')
pc.delete_collection("example-collection")

You can delete a collection using the Pinecone console.