"Pinecone aligns with our vision to democratize data accessibility for all engineers, and we're excited to uncover more potential with its new serverless architecture.

Pinecone is the leading vector database for building accurate and performant AI applications at scale in production.

This guide shows you how to set up and use Pinecone Database for high-performance semantic search. To get started in your browser, use the Quickstart colab notebook. To try Pinecone Database locally before creating an account, use Pinecone Local.

Reliable With a 99.95% uptime SLA, Pinecone is trusted by leading startups and enterprises for their production AI applications.

When you query a dense index, Pinecone retrieves the dense vectors that are the most semantically similar to the query. This is often called semantic search, nearest neighbor search, similarity search, or just vector search.

Feb 8, 2022 · Pine cones come in all shapes, sizes and shades of brown. The conical or cylindrical woody cones help identify the species of pine trees. Most pine cones have an overall cone-like or egg shape. Some seed cones from pine trees are long and cylinder-like, whereas other pine cones are more egg-shaped with woody spiny scales. Some of the smallest pine …

Sep 17, 2024 · The different types of pine cones can be found across various species of pine trees, each adapted to specific environments.

Mar 17, 2025 · Pinecone is a powerful vector database that simplifies search for AI applications. It offers unmatched speed and scalability for projects related to natural language processing, semantic search, or recommendation systems.

May 1, 2025 · Building high-performance vector search applications requires frameworks and tools that can handle concurrent operations effectively. In this article, we'll explore the benefits of using Pinecone's Python SDK with FastAPI, a web framework for building high performance APIs in Python and asyncio.

Dec 22, 2024 · Pinecone is a cloud-native vector database designed for managing and searching through vector embeddings efficiently. Unlike traditional relational databases, which are optimized for structured data and SQL queries, Pinecone is specifically built to handle high-dimensional vector data at scale.