From the course: Introduction to AI-Native Vector Databases
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Challenge: CRUD and performance
From the course: Introduction to AI-Native Vector Databases
Challenge: CRUD and performance
In this chapter, we explained how vector databases search over billions of objects in real-time. We introduced how the HNSW algorithm helps accomplish this, and we introduced how to perform real-time CRUD operations in Weaviate to ensure that our data is up to date. Now, for this challenge, we'll demonstrate the true power of vector databases at scale. Use the starter notebook and write code to help you first use the URL and API key to connect to the Weaviate instance. Second, identify how many vectors are stored in this database. Third, perform a search to find concepts you're interested in and see if you can filter out for a particular language that you understand, and then perform a vector search to see if you get back relevant results. Take some time to work on this challenge, and once you've come up with a solution, meet me in the next video, where I'll walk you through what I did.
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