Milvus

1. What is Milvus

   Overview of the Milvus vector database and its use cases.

2. Architecture

   Separation of storage and compute, node roles and data flow.

3. Collections

   Creating and managing collections and databases.

4. Schema and Fields

   Field types, primary keys, dynamic fields and vector fields.

5. Insert, Upsert and Delete

   Writing, updating and deleting entities.

6. Indexes

   Index types such as HNSW, IVF and DiskANN, metric types and index selection.

7. Vector Search

   ANN search, search parameters, metric types and output fields.

8. Filtered Search and Query

   Scalar filter expressions combined with vector search.

9. Hybrid and Full-Text Search

   Sparse/dense hybrid search, full-text search and reranking.

10. Partitions

    Partitioning data to narrow search scope and manage data.

11. Consistency Levels

    Tunable consistency levels and their trade-offs.

12. Authentication and RBAC

    User authentication, roles, privileges and TLS.

13. Scaling and Deployment

    Standalone, distributed and managed deployment options and scaling.

Each section links to the official page. Titles and summaries by Extra Credit; the docs belong to their authors.