Qdrant Tutorial Repository
Basic Tutorials
Get up and running with Qdrant in minutes.
| Tutorial | Objective | Stack | Time | Level |
|---|---|---|---|---|
| Qdrant Local Quickstart | Basic CRUD operations and local deployment. | Python | 10m | Beginner |
| Semantic Search 101 | Build a search engine for science fiction books. | Python | 5m | Beginner |
Search Engineering Tutorials
Master vector search modalities, reranking, and retrieval quality.
| Tutorial | Objective | Stack | Time | Level |
|---|---|---|---|---|
| Semantic Search Intro | Deploy a search service for company descriptions. | FastAPI | 30m | Beginner |
| Hybrid Search with FastEmbed | Combine dense and sparse search. | FastAPI | 20m | Beginner |
| Relevance Feedback | Relevance Feedback Retrieval in Qdrant | Python | 30m | Intermediate |
| Collaborative Filtering | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate |
| Multivector Document Retrieval | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate |
| Retrieval Quality Evaluation | Measure quality and tune HNSW parameters. | Python | 30m | Intermediate |
| Hybrid Search with Reranking | Implement late interaction and sparse reranking. | Python | 40m | Intermediate |
| Semantic Search for Code | Navigate codebases using vector similarity. | Python | 45m | Intermediate |
| Multivectors and Late Interaction | Effective use of multivector representations. | Python | 30m | Intermediate |
| Static Embeddings | Evaluate the utility of static embeddings. | Python | 20m | Intermediate |
Operations & Scale
Production-grade management, monitoring, and high-volume optimization.
| Tutorial | Objective | Stack | Time | Level |
|---|---|---|---|---|
| Snapshots | Create and restore collection snapshots. | Python | 20m | Beginner |
| Data Migration | Move embeddings to Qdrant. | CLI | 30m | Intermediate |
| Embedding Model Migration | Use your new model with zero downtime. | None | 40m | Intermediate |
| Large-Scale Search | Cost-efficient search for LAION-400M datasets. | None | 48h | Advanced |
| Qdrant Cloud Prometheus Monitoring | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate |
| Self-Hosted Prometheus Monitoring | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate |
Develop & Implement
Core tools and APIs for building with Qdrant.
| Tutorial | Objective | Stack | Time | Level |
|---|---|---|---|---|
| Bulk Operations | High-scale ingestion approaches. | Python | 20m | Intermediate |
| Async API | Use Asynchronous programming for efficiency. | Python | 25m | Intermediate |
Migrate to Qdrant
Move your vectors from other databases and keep them in sync.
| Tutorial | Objective | Stack | Time | Level |
|---|---|---|---|---|
| Migration Tool Overview | Migrate vectors from any supported source. | CLI | Varies | Intermediate |
| From Pinecone | Migrate from Pinecone serverless indexes. | CLI | 15m | Intermediate |
| From Weaviate | Migrate from Weaviate (pre-create collection). | CLI | 20m | Intermediate |
| From Milvus | Migrate from Milvus/Zilliz with partitions. | CLI | 15m | Intermediate |
| From Elasticsearch | Migrate dense vectors from Elasticsearch. | CLI | 15m | Intermediate |
| From pgvector | Migrate from PostgreSQL pgvector tables. | CLI | 15m | Intermediate |
| Migration Verification | Verify data integrity and search quality. | Python | 1h+ | Intermediate |
| Keeping Postgres in Sync | Keep Postgres and Qdrant in sync. | Python | 30m | Intermediate |