Vector DB Sizing
Estimate vector database storage and costs
Vector Database Options
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What is Vector DB Sizing?
Vector databases store embeddings for semantic search. Storage requirements depend on vector count, dimensions, index type, and metadata. This calculator helps you estimate requirements before choosing a database.
Understanding these factors helps you choose between self-hosted and managed solutions, and right-size your infrastructure.
Index Types
HNSW
Hierarchical Navigable Small World. Fast queries, ~50% storage overhead. Best for most use cases.
IVF
Inverted File Index. Balanced speed/accuracy, ~20% overhead. Good for large datasets.
Flat
Exact search, no overhead. Slow for large datasets but perfect accuracy.
FAQ
How much RAM do I really need?
For in-memory databases, plan for 1.3-1.5x your total storage. Disk-based solutions need less RAM but are slower.
Self-host or managed?
Under 10M vectors: managed is often simpler. Above 10M: self-hosting can save 50%+ on costs.