Hi everyone,
I'm currently working on setting up a robust data integration solution using CData's drivers in a corporate environment, and I'm encountering some challenges in optimizing performance. Our infrastructure includes a mix of cloud and on-premises data sources, and we're using a rack server setup for the on-prem data center. The server hosts multiple virtual machines that are running data connectors to sync data with our cloud-based systems.
The issue I'm facing is data throughput and latency. Although our rack servers are equipped with ample processing power and memory, I’ve noticed that data transfers between on-prem databases (SQL Server and MySQL) and cloud systems (like Salesforce and Azure SQL) seem to be slower than expected. I'm wondering if anyone here has experienced similar issues or has recommendations on how to fine-tune performance in this type of server environment?
Some of the steps I’ve already tried:
- Configuring the connection properties within the CData ODBC drivers to optimize for bulk data loads.
- Ensuring that the rack server’s network is optimized (e.g., using high-speed switches and ensuring minimal latency between VM hosts).
- Adjusting connection pooling and query timeouts, though results have been mixed.
If anyone has had success improving performance in a similar setup, or if there are specific settings within the CData drivers that I might have overlooked, I’d appreciate your insights. Thanks in advance!
Looking forward to hearing your thoughts.
