Pinecone Systems' new vector database provide similarity search as a  cloud service. Use cases include recommendations, personalization, image search, and deduplication of records. 

A vector, or vector embedding, is a string of numbers that represents documents, images, or other data. Vectors are used in the development of machine learning applications. A vector database stores, searches, and retrieves the representations by similarity or by relevance.

Pinecone’s vector database is accessed through an API. Early adopters range from startups to large companies with machine learning initiatives that need to scale. 

Pinecone Systems’ lead investor was also an early investor in Snowflake, and the similarities don’t stop there. 

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