Release notes
This document contains details about Pinecone releases. For information about using specific features, see our API reference.
April 25, 2022
Partial updates (Public Preview)
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.
New metrics
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:
pinecone_vector_count
pinecone_request_count_total
pinecone_request_error_count_total
pinecone_request_latency_seconds
pinecone_index_fullness
(Public Preview)
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 Connector
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.
Support for Boolean and float metadata in Pinecone indexes
You can now add Boolean
and float64
values to metadata JSON objects associated with a Pinecone index.
New state field in describe_index results
The describe_index
operation results now contain a value for state
, which describes the state of the index. The possible values for state
are Initializing
, ScalingUp
, ScalingDown
, Terminating
, and Ready
.
Delete by metadata filter
The Delete
operation now supports filtering my metadata.