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+# Overhead
+
+Narwhals converts Polars syntax to non-Polars dataframes.
+
+So, what's the overhead of running pandas vs pandas via Narwhals?
+
+Based on experiments we've done, the answer is: it's negligible. Here
+are timings from the TPC-H queries, comparing running pandas directly
+vs running pandas via Narwhals:
+
+[Comparison of pandas vs "pandas via Narwhals" timings on TPC-H queries showing neglibile overhead](https://github.com/narwhals-dev/narwhals/assets/33491632/71029c26-4121-43bb-90fb-5ac1c16ab8a2)
+
+[Here](https://www.kaggle.com/code/marcogorelli/narwhals-tpc-h-results-s-2-w-native)'s the code to
+reproduce the plot above, check the input
+sources for notebooks which run each individual query, along with
+the data sources.
+
+On some runs, the Narwhals code makes things marginally faster, on others
+marginally slower. The overall picture is clear: with Narwhals, you
+can support both Polars and pandas APIs with little to no impact on either.
+
+A fairly common question we receive is "why not just use Ibis". We believe
+that Ibis works well as a SQL frontend, but find [its overhead when translating
+dataframe APIs](https://github.com/ibis-project/ibis/issues/9345) to be unacceptably high -
+that's why we created something new.