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@@ -46,15 +46,11 @@ Exact RAM usage is difficult to predict precisely, but this formula gives a reas
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num_vectors * dimensions * 4 bytes * 1.5
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num_vectors * dimensions * 4 bytes * 1.5
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```
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```
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Quantization can reduce this estimate by a factor of 4 to 32, depending on the quantization method.
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Quantization can reduce this estimate by a factor of 4 to 32, depending on the quantization method. See [Quantization](/documentation/manage-data/quantization/) for the tradeoffs between quantization methods, and monitor actual memory usage before and after resizing (see [Monitor Collection Memory Usage](/documentation/ops-monitoring/memory-usage/)).
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<aside role="status">
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<aside role="status">To get a more detailed sizing estimate, try the <a href="https://sizing.qdrant.tech/estimate">Qdrant Sizing Calculator</a>.</aside>
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To get a more detailed sizing estimate, try the <a href="https://sizing.qdrant.tech/estimate">Qdrant Sizing Calculator</a>.
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</aside>
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On top of the vector data itself, budget for the HNSW index, which typically adds 20% to 30% overhead, along with payload indexes and the write-ahead log. Reserve about 20% headroom for optimizer operations and operating system cache.
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<aside role="status"> On top of the vector data itself, budget for the HNSW index, which typically adds 20% to 30% overhead, along with payload indexes and the write-ahead log. Reserve about 20% headroom for optimizer operations and operating system cache.</aside>
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See [Quantization](/documentation/manage-data/quantization/) for the tradeoffs between quantization methods, and monitor actual memory usage before and after resizing (see [Monitor Collection Memory Usage](/documentation/ops-monitoring/memory-usage/)).
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## When Vertical Scaling Is No Longer Enough
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## When Vertical Scaling Is No Longer Enough
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