Software Toolbox Technical Blog

If you’re an existing user or you’ve been keeping up with our previously released Cogent DataHub blogs, you’re already aware that Cogent DataHub is renowned for its extensive connectivity options to industrial data systems, but most importantly its secure, high performance, scalable, firewall, DMZ, & proxy friendly data transfer within premises and to/from the cloud. However, it’s worth emphasizing that DataHub’s connectivity includes MQTT, IoT, OPC DA, OPC UA, OPC UA Alarms & Conditions, OPC Classic Alarms & Events, Modbus, Excel, ODBC & more. These methods of connectivity help users realize that with DataHub, data has the freedom to seamlessly and securely traverse across various platforms. We truly believe that "once the data is in DataHub, it can go anywhere, securely".

In this blog post, I'll provide insight into using DataHub’s Transform property to manipulate data that is being logged to a database table. To follow along with this blog, as a prerequisite, you will need to have an ODBC database configured and have DataHub set up to be writing to that database. For more information on connecting and writing to a database, please read our blog “DataHub – 5 Quick Steps to Writing to a Database Table”. Unlike loggers that only work with OPC data sources, DataHub’s capability to securely tunnel data and aggregate from diverse sources besides OPC empowers many different types of applications.

If you've been keeping up with our previously released Cogent DataHub blogs, you're already aware that Cogent DataHub is renowned for its extensive connectivity. However, it's worth emphasizing that DataHub's connectivity includes MQTT, IoT, OPC DA, OPC UA, OPC UA Alarms & Conditions, OPC Classic Alarms & Events, Modbus, Excel, ODBC & more. These methods of connectivity help users realize that with DataHub, data has the freedom to seamlessly traverse across various platforms. We truly believe that "once the data is in DataHub, it can go anywhere, securely".

Developers that have leveraged our OPC Data Client toolkit for their custom OPC client development needs know that we’ve historically supported Python as a COM development language, but that had always come with limitations and a desire from our user base for a more modern option.

In the latest V2023.2 release, OPC Data Client now adds support for Python.NET, while also announcing the deprecation of the older COM approach. The newer Python.NET option offers many advantages including, but not limited to:

• Modern, maintained Python.NET package (pythonnet), instead of the older pypiwin32 package
• Added performance and reliability that comes from using the OPC Data Client .NET API over the COM API
• Access to .NET features, such as generics, methods overloads, and callbacks
• Easier coding

With the added support for Python.NET, we have also added more than 270 Python.NET examples to make it as easy as possible for our users to learn how this works within our product. PyCharm is now listed as one of the primary development environments.

Now that we have a basic understanding of the advantages that Python.NET has over its predecessor, let’s see it in action!

Whether you're running a production system in manufacturing, oil and gas, building automation, or energy, safety and uptime are of the utmost importance, especially with cybersecurity attacks increasing in frequency and complexity.

That’s why when running an application with widespread user access, managing user permissions and configurations is so important, and you need a solution that is as security centric as you are. In this blog post, we delve into how to manage user groups and permissions inside the TOP Server’s User Manager and Security Policies Plug-In to ensure a robust and secure gateway to your TOP Server Configuration.