Processing Concurrent Future - Multi Processing is slower than Synchronous Approach in Python

I want to process a list of 1 million documents in Python Concurrent Future. But I see it consumes lot of time than a normal synchronous approach. Below is the sample code snippet with detail.

Code to create a list of dictionary

data = []

for i in range(1, 1000000):
    data.append({"_id":i, "name":"MaxPayne "+str(i)})

Helper function to print text

def printText(d):
    return d

Synchronous way

for i in data:
    x=printText(i["name"])
    print(x)

Sychronous way takes 8 seconds to process entire list and print the data

Concurrent Future Processpool

with concurrent.futures.ProcessPoolExecutor() as executor:
     results = [executor.submit(printText, d["name"]) for d in data]

     for f in concurrent.futures.as_completed(results):
         print(f.result())

Concurrent Future way takes 300 seconds to process entire list and print the data

May I know what is the issue. Can any one help me fixing this bug. Thanks in Advance