Todd Loomis

Six years ago I was asked to implement a data repository to hold network management and performance data. With monitoring systems, databases have a tendency to be large, and have a delicate balance between inserting (logging) new data and deleting old (aging) data out from the system. The SQL Anywhere server database from iAnywhere was what the customer wanted to use, so I first had to evaluate if it could handle the expected load. It was initially estimated that the solution would need to support 20 to 30 gigabyte databases, where data collection was ongoing and older data was deleted on a rolling window of 30 days. No problem - one gigabyte of data a day in, one gigabyte of data a day out. I easily validated that SQL Anywhere could handle the load. Over the next year, performance requirements doubled, then redoubled again. Currently, I now support many 100-plus gig... (more)

Achieving Higher Throughput with SQL Anywhere

Six years ago I was asked to implement a data repository to hold network management and performance data. With monitoring systems, databases have a tendency to be large, and have a delicate balance between inserting (logging) new data and deleting old (aging) data out from the system. The SQL Anywhere server database from iAnywhere was what the customer wanted to use, so I first had to evaluate if it could handle the expected load. It was initially estimated that the solution would need to support 20 to 30 gigabyte databases, where data collection was ongoing and older data was ... (more)