Releasesby GlyphDeploy pg\_pinecone to Render or Railway
Pinecone released one-click templates to deploy pg_pinecone on Render or Railway running PostgreSQL 18 with preloaded vector extensions.
Also shipped Nov 13, 2026Pinecone in November 2026 →
AI Function task support in Declarative Automation Bundles (Beta)
Databricks introduced Beta support for AI Function tasks within Declarative Automation Bundles.
Give agents only the access they need
Buildkite released token permissions and queue scopes for agent tokens, allowing teams to restrict agent capabilities and limit job acceptance to specific queues.
Many-to-many relationships in semantic views (Preview)
Snowflake Cortex AI launched a public preview for modeling many-to-many relationships between logical tables within semantic views.
BigQuery connections for MySQL, Oracle, and PostgreSQL are in preview
Google Cloud introduced BigQuery federated query connections to MySQL, Oracle, and PostgreSQL in public preview.
Upcoming deprecation of selected GitHub Copilot models in December
GitHub announced the upcoming deprecation of several Copilot models on December 14, 2026, including Claude Fable 5, Gemini 3.8 Flash, and Grok 4.6.
Aurora PostgreSQL with express configuration now supported in CloudFormation
AWS added support for Aurora PostgreSQL express configuration in CloudFormation, enabling single-property automated cluster creation and faster serverless database setup.
More from Pinecone platformEvery Pinecone platform release →
Released Java SDK v6.3.0
Pinecone released version 6.3.0 of its Java SDK, resolving 33 security advisories in dependencies and fixing a bug where clients sharing a JVM with different API keys could share index connections.
Search by meaning in pg\_pinecone
pg\_pinecone can now embed a table's text column with a hosted model, such as gemini-embedding-2, so you can search by meaning without a vector column. It's available in v0.12.1. To upgrade an existing install, see the operator runbook.
New embedding models for document indexes
Pinecone document indexes now support Google's gemini-embedding-2 and OpenAI's text-embedding-3-small and text-embedding-3-large models.
Twice the included embedding tokens through December 31
Pinecone is doubling the included monthly embedding tokens for Starter and Builder organizations through December 31, 2026.
Released pg\_pinecone
The pg_pinecone extension is now available, enabling native vector search within PostgreSQL. It allows users to perform vector searches using the local engine or offload indexing to Pinecone for larger datasets.
Released Pinecone Terraform Provider v5.1.0
Released v5.1.0 of the Terraform Provider for Pinecone. This version adds integrated embedding for document indexes, so Pinecone can embed a string field's text with a hosted model. It also adds on-demand read capacity for BYOC indexes. Indexes created with the top-level embed attribute are now called legacy integrated indexes.
Export usage and cost data with the Admin API
Enterprise organizations can now export usage and cost data through the Admin API as an alternative to downloading a CSV from the console. Create an export covering any period in the last 365 days, poll it until it finishes, then download the zip archive of FOCUS v1.4 CSV files. For the steps, see Download a usage report.
Released Pinecone Terraform Provider v5.0.0
Released v5.0.0 of the Terraform Provider for Pinecone. This version uses API version 2026-07 and adds the schema style for describing indexes, with the schema and deployment attributes. Use it to manage document indexes with dense vector, sparse vector, and full-text-search fields.