update costeffectiveness

index.html

@@ -216,8 +216,11 @@ <h1>Comparison of Vector Databases</h1>
         </td>
     </tr>
     <tr>
-        <td>Cost effectiveness of vector search (lower is better)
-            <span class="note">This is the cost of running the benchmark on a cloud provider. Provided by <a href="https://myscale.github.io/benchmark/">MyScale</a></span>
+        <td>
+            Monthly Cost Per 100 QPS (Lower Is Better)
+            <span class="note">
+                Indicates the monthly expense to achieve 100 Queries Per Second on a 5M 768D vector dataset with each vector database cloud service. Lower costs represent higher cost-effectiveness. Benchmark data provided by <a href="https://myscale.github.io/benchmark/">MyScale</a>.
+            </span>
         </td>
         <td>30</td>
         <td>181</td>
@@ -229,8 +232,11 @@ <h1>Comparison of Vector Databases</h1>
         <td>616</td>
     </tr>
     <tr>
-        <td>Cost effectiveness of filtered vector search (lower is better)
-            <span class="note">This is the cost of running the benchmark on a cloud provider. Provided by <a href="https://myscale.github.io/benchmark/">MyScale</a></span>
+        <td>
+            Monthly Cost Per 100 QPS for Filtered Vector Search (Lower Is Better)
+            <span class="note">
+                Reflects the monthly cost for achieving 100 Queries Per Second on a 5M 768D vector dataset with metadata filtering in each vector database cloud service. Lower costs indicate more cost-efficient handling of filtered searches. Benchmark details available at <a href="https://myscale.github.io/benchmark/">MyScale</a>.
+            </span>
         </td>
         <td>83</td>
         <td>449</td>