The difference in performance that you observed between the Python Connector and JDBC driver could be due to the difference in the way they handle connections, data conversion and queries.
You may consider profiling the code execution and examining the query plans generated by both of them to get more insights.
Please go through the following blog that shares performance tuning techniques for Amazon Redshift : https://aws.amazon.com/blogs/big-data/top-10-performance-tuning-techniques-for-amazon-redshift/
You may also check the below GitHub links for the above drivers :
- aws/amazon-redshift-jdbc-driver - https://github.com/aws/amazon-redshift-jdbc-driver/issues
- aws/amazon-redshift-python-driver - https://github.com/aws/amazon-redshift-python-driver/issues
[+] Configuring connections in Amazon Redshift - https://docs.aws.amazon.com/redshift/latest/mgmt/configuring-connections.html
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