“For structured data with straightforward applications, users should stick to traditional relational databases or NoSQL databases. A vector database becomes essential when handling unstructured ...

The SQL queries in Rockset allow combining vector search with other metadata filters. The query optimizer in Rockset picks whether to use KNN or ANN under the hood based on the query and data to ...

Just a few “native” vector databases existed prior to ChatGPT, such as Pinecone, Milvus, and Zilliz.But almost overnight, many existing database vendors adapted their wares to be able to store, index, ...

Azure SQL Database now supports native vector storage and processing, streamlining AI development by integrating vector search with SQL queries. This update simplifies database management ...

Vector databases: a distinct type of database for the generative AI era. ... That happened with relational databases and no-SQL databases, and that’s happening with vector databases, he said.

There is no universal ‘best’ vector database—the choice depends on your needs. Evaluating scalability, functionality, performance, and compatibility with your use cases is vital.

Vector databases and search aren’t new, but vectorization is essential for generative AI and working with LLMs. Here's what you need to know. One of my first projects as a software developer was ...

But AI systems that rely on vector databases are introducing risks faster than the defenders can keep up. Security, privacy and compliance teams are on their heels trying to catch up.

These include updates to its Spanner SQL database, which now features graph and vector search support, as well as extended full-text search capabilities. This wouldn’t be a Google announcement ...