Tap into historical data and accelerate analytics with version 2.2
Aron Semle
is the Chief Technology Officer of HighByte, focused on guiding the company’s product strategy through research and development and technical evangelism.
When I first joined the HighByte team, I knew two things. First, modeling industrial data is immensely powerful. After spending a decade interacting with tags and seeing firsthand how building context from tags in the Cloud is painful, I knew that modeling data at the Edge would be a game changer.
The second thing I knew is that we were going to build a lot of connectors. This is par for the course in the industrial world where a mix of legacy and new equipment is the norm. We started with the most common and generalized standards, like OPC UA, HTTP, MQTT, and SQL to cast a wide net for connectivity options inside the factory. But it was clear that as we progressed, the market would demand explicit connectors for common systems.
That is why I am excited to announce new connectors in version 2.2 for OSIsoft PI System (now part of the AVEVA portfolio), InfluxDB, and Oracle Database. All three connectors support both reading and writing data, and interacting with these systems in advanced ways, without needing to read a manual.
The second thing I knew is that we were going to build a lot of connectors. This is par for the course in the industrial world where a mix of legacy and new equipment is the norm. We started with the most common and generalized standards, like OPC UA, HTTP, MQTT, and SQL to cast a wide net for connectivity options inside the factory. But it was clear that as we progressed, the market would demand explicit connectors for common systems.
That is why I am excited to announce new connectors in version 2.2 for OSIsoft PI System (now part of the AVEVA portfolio), InfluxDB, and Oracle Database. All three connectors support both reading and writing data, and interacting with these systems in advanced ways, without needing to read a manual.
The new PI connector is being used by one of our customers to query and mix aggregated data from PI (min, max, average, etc.) with real-time data from PLCs. Another customer is querying years of historical data, modeling it, and sending it to an advanced AI/ML platform to train AI models. And yet another customer is integrating third party sensor data from the Cloud back into the factory and writing the modeled data directly into PI’s Asset Framework. These use cases illustrate how the Intelligence Hub can accelerate analytics for batch and process manufacturers.
The new InfluxDB connector is being used to store data from the unified namespace (UNS) in InfluxDB, run calculations on it, and push the results back into the UNS. It is a seamless and effortless way to add historical data to the UNS.
Finally, the new Oracle Database connector allows users to connect to MES and ERP systems backed by Oracle Database, and both read and write data to these systems.
And that’s just scratching the surface of the new capabilities packed into this release. Let’s jump into the highlights of HighByte Intelligence Hub version 2.2.
The new InfluxDB connector is being used to store data from the unified namespace (UNS) in InfluxDB, run calculations on it, and push the results back into the UNS. It is a seamless and effortless way to add historical data to the UNS.
Finally, the new Oracle Database connector allows users to connect to MES and ERP systems backed by Oracle Database, and both read and write data to these systems.
And that’s just scratching the surface of the new capabilities packed into this release. Let’s jump into the highlights of HighByte Intelligence Hub version 2.2.
Release Highlights
- PI System. The new PI connector uses the OSIsoft PI AF SDK to connect, read, and write to PI System. The connector supports reading raw points, aggregates, event frames, and assets. It also supports writing HighByte Intelligence Hub instances to PI Points or as Elements and Templates directly to Asset Framework.
- InfluxDB. The new InfluxDB connector supports reading from InfluxDB using the Flux query language, as well as writing modeled data into InfluxDB. InfluxDB tags are also supported, allowing customers to structure the InfluxDB data using the ISA-95 hierarchy.
- Oracle Database. Oracle is now a first-class connection, just like SQL Server, PostgeSQL, and MySQL. The new Oracle connector supports reading and writing to Oracle Database, as well as calling stored procedures.
- CSV Outputs. The new CSV output feature allows customers to easily output modeled data to a CSV file to verify a flow is working, as well as push modeled data to new AI/ML platforms for training. In this case, the training and real-time data flows in HighByte Intelligence Hub are different, but both use the same standardized data model. This is the power of data modeling at the Edge!
- SAML. The Intelligence Hub now supports integration with third party identity providers using Security Assertion Markup Language (SAML). This allows customers to control login credentials and user roles in applications like Active Directory, Okta, or PingID. The Intelligence Hub then authenticates users through the third party IdP and limits what the user can do depending on their assigned roles in the Intelligence Hub.
- OPC UA Subscriptions. This release enhances the OPC UA connection to include support for OPC UA Subscriptions. This makes connecting to resource constrained OPC UA servers like PLCs easier and more efficient.
- Enhanced Array Expansion. A single HighByte Intelligence Hub instance can now input an array of data (e.g., SQL rows), transform each row through the instance, and output the transformed array using the new Instance Mode setting. In prior releases, this type of transformation required a child instance/model hierarchy.
- MQTT Topics. This release includes a new “Include Topic” setting to the MQTT Input, allowing customers to capture the topic name and use it in instance expressions. This is commonly used when the MQTT topic namespace includes ISA-95 hierarchy that is required in upstream systems.
- Breakup Arrays. MQTT and Sparkplug outputs were enhanced with the new “Breakup Arrays” feature, allowing arrays of data (e.g., SQL rows) to be output as individual publishes. When combined with dynamic outputs, this allows the connections to break an array into different publishes on different topics.
- Log4j Security Updates. Log4j is an open-source library used by many Java applications to write log messages to various output formats. Previous versions of the Intelligence Hub used Log4j to write log messages out to the console as well as a flat-file database. Recently, multiple security vulnerabilities were discovered in the library that could allow an attacker to execute arbitrary code when log messages are evaluated. We have addressed these issues in HighByte Intelligence Hub version 2.2.0 by removing our direct dependency on Log4j. This component was replaced with proprietary logging technology that provides the same capabilities and limits the scope to only those capabilities needed by the Intelligence Hub. We recommend that all customers upgrade to version 2.2.0 (Build 2021.12.22.75) to take advantage of this fix.
Additional Resources
We hope you are as excited as we are about the new use cases we’ve enabled in HighByte Intelligence Hub version 2.2. This release provides users with more connectivity and data transformation options and accelerates analytics for batch and process manufacturers. To learn more, check out these additional resources:
- Register for the release webinar on January 13, 2022.
- Read the release notes for details on new features and fixes.
- Request a free trial or log in to your existing account to test the software in your unique environment.
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