In an interview with Datanami, Freedman also singled out Pinecone, which develops a dedicated vector database, as a new competitor.The problem with dedicated vector databases, Freedman says, is that ...

High-performance open-source vector database Qdrant today announced it’s launching a new managed hybrid cloud model of its database to power enterprise artificial intelligence apps under the ...

While other vector database companies use Splade, Vasnetsov said BM42 is a more cost-efficient solution. “Splade can be very expensive because these models tend to be really huge and require a ...

The vector database market is experiencing rapid growth, with projections estimating it will reach $10.6 billion by 2032, according to market research firm SNS Insider.

And no vector database company was hotter than New York City-based startup Pinecone, which raised $100 million last April and led the way in a competitive landscape.

The mighty Z80 processor ran the code at astounding speed, proving retro-tech got a lot of things right A Microsoft senior ...

Like NoSQL, vector databases also specialize in unstructured data types (e.g., images, videos, social media posts), but are particularly well suited to large language models (LLMs) and generative AI.

Data Cloud Vector Database will unify all business data, including unstructured data like PDFs, emails, and transcripts, with CRM data to enable grounding of AI prompts and Einstein Copilot ...

A vector database becomes essential when handling unstructured data requiring complex algorithmic work, such as high-dimensional data, similarity searches, real-time AI applications, or when ...

The company’s database supports a broad range of tasks and data types including transactions, AI, edge computing, vector search, full-text search, operational data, streaming data, time-series ...

Enter vector databases, a new solution designed to handle unstructured data in a way that feels intuitive and context-aware. By representing data as mathematical embeddings—essentially capturing ...

We save the title, a chunk from the body, and the embedding vector for the chunk in a row of the database. For each article, there are as many vectors as there are chunks. We index the vector ...