Index Comparison

Same data, same query — 6 different strategies side by side

Shared Input

All 6 indexes use exactly these values. Change any number to see how each index responds differently.

🎯 Query

Stored Vectors

sim

Vector A

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Vector B

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Vector C

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Vector D

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Vector E

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Vector F

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🎓 Tips 3 tips

No single "best" index. Each index trades off speed, accuracy, and memory differently, the right choice depends on your dataset size and latency needs.

Try changing the query vector, the ranking of similarity scores stays the same across indexes since they all approximate the same underlying search.

FLAT is the baseline. Every other index is a shortcut that sacrifices some exactness for speed, compare their results here to see how close they get.

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Key Takeaway

Different vector index strategies make different speed vs. accuracy vs. memory trade-offs, comparing them side by side helps you pick the right one for your use case.

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