Well now, the explosion of vector databases is overwhelming (yes, not just “whelming”).
I have been playing around with PostgreSQL pg-vector but if you use Microsoft SQL for your main day-to-day stuff, then vector support is coming! It is in preview for Azure SQL databases as well as SQL 2025 (preview).
Okay, if you are not sure what a vector even is (in AI terms) then:
In artificial intelligence (AI), a vector is a mathematical representation of data, such as words, images, or other entities, in a multi-dimensional space. Each vector consists of a list of numbers that capture the essential features or characteristics of the data it represents. This numerical representation allows AI models to process and analyze complex information more effectively.
Vectorizing Words:
To enable AI systems to understand and manipulate human language, words are converted into vectors through a process called word embedding. This process involves mapping each word to a high-dimensional vector space, where words with similar meanings are positioned closer together. For example, the words "king" and "queen" would be represented by vectors that are near each other in this space, reflecting their semantic similarity.
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