Sessionless and stateless web application
No server-side stay-in-memory objects
File data saved using the file or database system
Database size is small and network bandwidth usage is optimized
Deploy WorkflowGen in a web farm environment with load balancing
Use multiple servers for web applications, files, and databases
Use a real-time replicated secondary database to reduce server response time (database scaling feature)
Totally compliant with load balancing and web farm architectures
Improves web server memory usage
WorkflowGen offers several options to optimize storage size and response time according to your constraints. For example:
You can reduce the amount of data displayed on the User Portal home page
You can define process data to keep all the versions of the data value by actions or only the late one
You can configure WorkflowGen to store file data in the database or in the file system. Database storage simplifies the file data administration and backup (without interruption of service).
File system storage provides the following benefits:
Optimizes the database size and database server CPU load
Reduces the network bandwidth usage between the web server and the database server
File data can be stored in a local or remote folder
WorkflowGen supports web farm configuration; you can set up two or more web servers to handle workflow requests. Web farm configuration improves the performance and offers high availability.
WorkflowGen provides a unique way to dramatically improve the response time of your processes thanks to database farms. In addition to the primary WorkflowGen database, you can set up another read-only database that is replicated with the Master database in close to real time. WorkflowGen will forward the read-only SQL queries to the Slave database, and because there are more “read” queries than “write” commands, product performance is dramatically improved.
Database scaling is supported only with SQL Server databases.
For heavy usage with thousands of transactions per hour, you can combine the previous features to build a highly scalable BPM architecture; for example:
Two load-balanced web servers
One master database server
Two slave database servers