Evaluating Which Python library is Best suitable for Bulk insert into Aurora Postgres SQL | Speed |

I wanted to share some of the results with you. To determine Which Python library gives us faster speed, we did a bulk insert into Aurora PostgreSQL using various library and result are mentioned in video

Article

GitHub Code:

Conclusion
SqlAlchemy should always be the primary option when working with and entering bulk items into AWS Aurora because it is obvious from testing that it is a faster approach to insert data into Aurora PostgreSQL. When compared to psycopg2(executemany), VS SqlAlchemy is almost 60 to 70% faster. Comparing batch Size 30,000 Bulk Insert using psycopg2(executemany) we found it took around 1248 seconds vs when using psycopg2(execute_batch_method ) took 19.4 seconds VS SQLAlchemy took only 1.5 seconds.

References

Aurora PostgreSQL Insert Many Performances Test Using Various Python Library. Accessed 27 Oct. 2022.

#aws #cloud #cloudcomputing #azure #devops #technology #python #amazonwebservices #linux #amazon #programming #awscloud #cybersecurity #coding #googlecloud #developer #kubernetes #bigdata #datascience #microsoft #machinelearning #software #java #tech #it #gcp #awstraining #javascript #security #docker

[praqash]

Bro, you are really setting some level in the tech tutorial world. I get to see something innovative and new every time i visit your channel. Thanks, subscribed!