Advanced
Deeper, power-user material for Ahnlich DB — how similarity algorithms work at the command level, how to choose between them, and how the pieces fit together end-to-end.
In this section
- Similarity algorithms — the linear metrics (cosine, euclidean) and the non-linear HNSW index, with configuration and tuning.
- Choosing & performance — comparison tables and benchmark-style trade-offs by data size and dimensionality.
- Command deep dive — how each command behaves in practice, for power users.
- End-to-end flow — create a store, insert data, build indexes, and query, start to finish.