diff --git a/asv_bench/benchmarks/merge.py b/asv_bench/benchmarks/merge.py
index ae27e8e400f..043de35bdf7 100644
--- a/asv_bench/benchmarks/merge.py
+++ b/asv_bench/benchmarks/merge.py
@@ -1,3 +1,5 @@
+import numpy as np
+
 import xarray as xr
 
 
@@ -13,6 +15,63 @@ def setup(self, existing_elements):
             d[f"var{i}"] = i
         self.dataset = xr.merge([d])
 
+        d = {f"set_2_{i}": i for i in range(existing_elements)}
+        self.dataset2 = xr.merge([d])
+
     def time_variable_insertion(self, existing_elements):
         dataset = self.dataset
         dataset["new_var"] = 0
+
+    def time_merge_two_datasets(self, existing_elements):
+        xr.merge([self.dataset, self.dataset2])
+
+
+class DatasetCreation:
+    # The idea here is to time how long it takes to go from numpy
+    # and python data types, to a full dataset
+    # See discussion
+    # https://github.com/pydata/xarray/issues/7224#issuecomment-1292216344
+    param_names = ["strategy", "count"]
+    params = [
+        ["dict_of_DataArrays", "dict_of_Variables", "dict_of_Tuples"],
+        [0, 1, 10, 100, 1000],
+    ]
+
+    def setup(self, strategy, count):
+        data = np.array(["0", "b"], dtype=str)
+        self.dataset_coords = dict(time=np.array([0, 1]))
+        self.dataset_attrs = dict(description="Test data")
+        attrs = dict(units="Celcius")
+        if strategy == "dict_of_DataArrays":
+
+            def create_data_vars():
+                return {
+                    f"long_variable_name_{i}": xr.DataArray(
+                        data=data, dims=("time"), attrs=attrs
+                    )
+                    for i in range(count)
+                }
+
+        elif strategy == "dict_of_Variables":
+
+            def create_data_vars():
+                return {
+                    f"long_variable_name_{i}": xr.Variable("time", data, attrs=attrs)
+                    for i in range(count)
+                }
+
+        elif strategy == "dict_of_Tuples":
+
+            def create_data_vars():
+                return {
+                    f"long_variable_name_{i}": ("time", data, attrs)
+                    for i in range(count)
+                }
+
+        self.create_data_vars = create_data_vars
+
+    def time_dataset_creation(self, strategy, count):
+        data_vars = self.create_data_vars()
+        xr.Dataset(
+            data_vars=data_vars, coords=self.dataset_coords, attrs=self.dataset_attrs
+        )