Efficient performance is one of the key metrics to evaluate any computer system, specifically a datastore. When dealing with large volumes of data, users expect a fast response time. However, you've constructed your datastore from scratch, and it may not match the speed or efficiency of enterprise-ready datastores like PostgreSQL or MongoDB. That's okay. Remember, 'Rome wasn't built in a day'. We need to adopt a performance-first mindset and focus on continual improvements.

Every operation, be it create, retrieve, update, or delete, could have performance bottlenecks that affect the speed. One of the simple ways to start improving performance is by measuring the current speed of operations. Python's built-in time module can measure time, which can be handy.

In Python, the time.time() function provides the current time. You can record the time before and after the operation and calculate the time elapsed for an operation.

Let's take an example. Below is a Python script which creates a dictionary with a million entries and then performs a retrieve operation. It measures the time taken to perform the operation.

This approach can form a baseline to guage how subsequent modifications to your architecture or code affect the efficiency. Continue to test performance as you add, modify, or optimize your datastore. Keep notes of your insights - these breadcrumbs will help you refine your datastore, just like how AI's are refined with each iteration.

Remember, the experience you gain here is the key. Improving performance is a combination of theory and practice. The same pattern of implementing, testing, optimizing used in financial models or AI algorithms, applies to datastores. It's this experience that allows us to confidently use and understand these systems, because we've built one ourselves. Slow and steady wins the race, right?

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import time

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if __name__ == '__main__':

    start_time = time.time()

    # Sample datastore

    datastore = {i : 'value'+str(i) for i in range(1000000)}

    # Retrieve operation

    print(datastore[999999])

    print('Operation took', time.time()-start_time, 'seconds.')