Database / Qdrant Vector DB Interview questions
What is a point in Qdrant?
A point is the basic unit of data stored in a Qdrant collection — a unique ID, one or more vectors, and an optional payload (a JSON object holding arbitrary structured metadata), roughly comparable to a row in a relational database.
client.upsert( collection_name="documents", points=[ models.PointStruct( id=1, vector=[0.05, 0.61, 0.76, 0.74], payload={"category": "news", "published": "2026-01-15"}, ) ], )
A point's ID can be either an unsigned integer or a UUID, and its vector must match the dimensionality declared for the collection (or, for a collection with named vectors, provide a value for each named vector it's expected to have).
Points are inserted, updated, and deleted through the same upsert-style operation — supplying a point with an existing ID overwrites that point's data — and every point's payload can be searched, filtered, and updated independently of its vector, which is what lets Qdrant combine vector similarity with structured filtering in a single query.
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