This document contains details about Pinecone releases. For information about using specific features, see our API reference.
You can now perform a partial update by ID and individual value pairs. This allows you to update individual metadata fields without having to upsert a matching vector or update all metadata fields at once.
Users on all plans can now see metrics for the past one (1) week in the Pinecone console. Users on the Enterprise and Enterprise Dedicated plan now have access to the following metrics via the Prometheus metrics endpoint:
Note: The accuracy of the
pinecone_index_fullness metric is improved. This may result in changes from historic reported values. This metric is in public preview.
Spark users who want to manage parallel upserts into Pinecone can now use the official Spark connector for Pinecone to upsert their data from a Spark dataframe.
You can now add
float64 values to metadata JSON objects associated with a Pinecone index.
describe_index operation results now contain a value for
state, which describes the state of the index. The possible values for
Delete operation now supports filtering my metadata.