Pinecone Azure support via the eastus-azure region is now generally available (GA).
Pinecone now supports deploying projects to Azure using the new eastus-azure region. This is a public preview environment, so test thoroughly before deploying to production.
The new gcp-starter
region is now in public preview. This region has distinct limitations from other Starter Plan regions. gcp-starter
is the default region for some new users.
Indexes in the starter plan now support approximately 100,000 1536-dimensional embeddings with metadata. Capacity is proportional for other dimensionalities.
Pinecone now supports new US and EU cloud regions.
Pinecone now supports SSO for Enterprise dedicated customers. Contact Support to set up your integration.
Pinecone now supports 40kb of metadata per vector.
Pinecone now supports vectors with sparse and dense values. To use sparse-dense embeddings in Python, upgrade to Python SDK version 2.2.0.
Python SDK version 2.2.0 with support for sparse-dense embeddings is now available on GitHub and PYPI.
You can now try out our new Node.js SDK for Pinecone.
You can now monitor your current and projected Pinecone usage with the Usage dashboard.
You can now sign up for Pinecone billing through Amazon Web Services Marketplace.
The latest release of the Python SDK makes the following changes:
batch_size
to the upsert methodPinecone Azure support via the eastus-azure region is now generally available (GA).
Pinecone now supports deploying projects to Azure using the new eastus-azure region. This is a public preview environment, so test thoroughly before deploying to production.
The new gcp-starter
region is now in public preview. This region has distinct limitations from other Starter Plan regions. gcp-starter
is the default region for some new users.
Indexes in the starter plan now support approximately 100,000 1536-dimensional embeddings with metadata. Capacity is proportional for other dimensionalities.
Pinecone now supports new US and EU cloud regions.
Pinecone now supports SSO for Enterprise dedicated customers. Contact Support to set up your integration.
Pinecone now supports 40kb of metadata per vector.
Pinecone now supports vectors with sparse and dense values. To use sparse-dense embeddings in Python, upgrade to Python SDK version 2.2.0.
Python SDK version 2.2.0 with support for sparse-dense embeddings is now available on GitHub and PYPI.
You can now try out our new Node.js SDK for Pinecone.
You can now monitor your current and projected Pinecone usage with the Usage dashboard.
You can now sign up for Pinecone billing through Amazon Web Services Marketplace.
The latest release of the Python SDK makes the following changes:
batch_size
to the upsert method