I tested LanceDB locally using Python. I created a database table named `support_docs`, inserted three sample records with vector values and text, and ran a similarity search using a query vector. The table was created successfully, all three records were stored, and the search returned results ordered by distance. This helped me understand the basic workflow for storing records and retrieving similar items using LanceDB. My testing was a small local technical evaluation rather than a production deployment. Review collected by and hosted on G2.com.

Some of the documentation can feel technical for beginners who are new to vector databases. A complete beginner-friendly example that covers installation, inserting data, generating embeddings, and performing semantic searches in one place would make the learning process easier. Review collected by and hosted on G2.com.