# Revision: Cheat Sheet and Self-Check — Vector Databases

Source: https://www.geekswithgeeks.com/en/vector-databases/z-revision

> Review the key ideas of the whole course.

## Cheat sheet

**What**: a vector database = durable storage + ANN index + payload filters + updates + operations; families: library, extension (pgvector), dedicated engine (Qdrant, Milvus, Weaviate, Chroma), managed service. **Model**: collection of records (id, vector, payload); same dimension and metric per collection; deterministic IDs. **pgvector**: `vector(n)`, operators `<->` L2, `<=>` cosine distance, `<#>` negative inner product; `ORDER BY ... LIMIT k`; match the operator class; SQL filters, joins, transactions, RLS, `halfvec`. **Indexes**: exact scan first (ground truth); HNSW (`m`, `ef_construction`, `ef_search`) vs IVFFlat (`lists`, `probes`); index can be larger than the vectors; measure recall@k vs exact. **Filtering**: post-filtering can return too few rows (we saw 0); iterative scans, partial indexes or partitions, filter-aware engines with payload indexes; hybrid search with RRF. **Scale**: batch idempotent ingestion; shard by hashed key (resharding moves most data); replicate, `W + R > N`; capacity = vectors + links + payload, times copies, plus headroom. **Operate**: tenant isolation in the database, TLS and encryption, least privilege; backups and tested restores; new model = new index with shadow comparison and rollback; monitor recall, latency percentiles, freshness, cost. **Choose**: start simple and exact; compare on your data at equal recall; honest benchmarks.

**Quiz:** You add a `WHERE tenant = 7` filter to an HNSW query and get zero rows although tenant 7 has data. What is the likely cause and a fix?

- [ ] The data was deleted by the index
- [x] Post-filtering of a small candidate list; enable iterative scans or use partial indexes/filter-aware search
- [ ] Vectors cannot be filtered
- [ ] The server clock is wrong

*Answer:* Post-filtering of a small candidate list; enable iterative scans or use partial indexes/filter-aware search. The index returns nearest candidates first; the filter then removes them.

**Quiz:** Which statement about HNSW tuning is correct?

- [ ] ef_search has no effect
- [x] Raising ef_search raises recall and latency; measure recall against exact search
- [ ] Lower ef_search always improves recall
- [ ] Recall cannot be measured

*Answer:* Raising ef_search raises recall and latency; measure recall against exact search. Recall and latency trade off along the ef_search knob.

**Quiz:** Your cluster keeps 3 copies of each shard. Which write and read settings guarantee you read your latest acknowledged write?

- [ ] Neither matters
- [ ] Write to 1 and read from 1
- [ ] Write to 1 and read from 2 only if lucky
- [x] Write to 2 and read from 2

*Answer:* Write to 2 and read from 2. W + R > N guarantees the write and read sets overlap.