Vector Database

Similar Image Search

Sometimes text search is not enough. Qdrant vector database allows you to find similar images, detect duplicates, or even find a picture by text description.

Qdrant filters enable you to apply arbitrary business logic on top of a similarity search. Look for similar clothes cheaper than $20? Search for a similar artwork published in the last year? Qdrant handles all possible conditions!

For the Demo, we put together a food discovery service - it will show you a lunch suggestion based on what you visually like or dislike. It can also search for a place near you.

Semantic Text Search

Full-text search does not always provide the desired result. Documents may have too few keywords, or queries might be too large.

One way to overcome these problems is a neural network-based semantic search, which can be used in conjunction with traditional search. The neural search uses semantic embeddings to find texts with similar meaning.

With Qdrant vector search engine, you can build and deploy semantic neural search on your data in minutes! Compare the results of a semantic and full-text search in our demo.

Recommendations

User behavior can be represented as a semantic vector is similar way as text or images. This vector can represent user preferences, behavior patterns, or interest in the product.

With Qdrant vector database, user vectors can be updated in real-time, no need to deploy a MapReduce cluster. Understand user behavior in real time.