API World + CloudX + Dev Innovation Summit 2024

Anil Inamdar, Instaclustr by NetApp, Head of Data Solutions

For dev teams building and training their own AI models, ending up with AI solutions plagued by hallucinations and reliability issues is a (rightfully) huge concern. The good news: vector databases make generative AI considerably more reliable and less prone to hallucinations. The even better news: a number of *100% free and open source* vector databases are especially great options for supporting AI workloads.

The good news keeps coming for teams considering an open source vector database path: it isn’t necessary to invest in implementing new or exotic or proprietary or specialized data-layer solutions to harness vector databases. Many enterprises will find that their existing infrastructure can already support AI workloads (while continuing to provide the familiar data availability, scalability, and performance they already know they can trust). In particular, PostgreSQL (with the pgvector extension), OpenSearch, and Apache Cassandra 5.0 (with its new native vector indexing) are three completely open source technologies—no proprietary or open core solutions needed—that tick all the boxes for meeting enterprises’ AI workloads requirements.

Attendees of this Dev Innovation Summit session will learn how open source vector databases utilize vector embeddings to enable more accurate LLMs, and how to strategically approach and implement retrieval augmented generation (RAG) processes. Attendees will also come away with a clear understanding of the advantages offered by PostgreSQL with pgvector, OpenSearch and Cassandra 5.0 as particularly mature open source vector database strategies ready to jumpstart your organization’s competitive AI capabilities.