Qdrant Has a Free API You Should Know About

Qdrant is an open-source vector database designed for AI applications. It stores and searches high-dimensional vectors with blazing speed — perfect for semantic search, recommendations, and RAG. Why Qdrant Powers Modern AI Apps A startup building a RAG chatbot was storing embeddings in PostgreSQL with pgvector. At 10M vectors, queries took 3 seconds. They switched to Qdrant — same queries now take 15ms. Key Features: Fast Search — HNSW algorithm for sub-millisecond queries Filtering — Combine vector similarity with metadata filters Payload Storage — Store arbitrary data alongside vectors Quantization — Reduce memory usage by 4-32x Distributed — Horizontal scaling with sharding Quick Start docker run -p 6333:6333 qdrant/qdrant Python SDK from qdrant_client import QdrantClient from qdrant_client.models import VectorParams, Distance client = QdrantClient("localhost", port=6333) client.create_collection( collection_name="articles", vectors_config=VectorParams(size=384, distance=Distance.CO