In the past year, embeddings have gained significant traction as a powerful technique in the fields of Machine Learning and Generative-AI. These embeddings serve as vector representations of data points, capturing their essential characteristics and features.
However, as the demand for efficient semantic search at a large scale increases, there arises a need for a robust platform capable of storing embeddings and enabling seamless search capabilities. Greenplum, a cutting-edge data warehousing solution now equipped with the performance-oriented pgvector. As an open-source extension for PostgreSQL, pgvector empowers customers to store ML embeddings, construct AI applications, and execute high-performing similarity searches.