Use the comparison tool below to compare the top Data Historians on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Fernhill Software
Free runtimeVROC
Iconics
GE Vernova
Canary
$9,970 one-time paymentFactry
AVEVA
eLynx Technologies
DEWESoft
AVEVA
Rockwell Automation
Codra
A data historian is a specialized type of software that allows users to store and analyze data from industrial processes. It collects, stores, and displays time-series process data from devices such as sensors, programmable logic controllers (PLCs), distributed control systems (DCSs), analyzers, and actuators. Data historians provide access to predefined reports for easy review of operational details or individual records for drilling down into specific events. Data historians can also be used to build custom analytical models with the ability to spot trends over longer periods of time.
Data historian software provides visibility into industrial operations by capturing normalized time-stamped data from many different sources which allows engineers to know what happened when and why it happened. This opens up possibilities for predictive maintenance, process optimization/automation, and other key improvements in efficiency or product quality. The vast amounts of data stored in the data historian also allow it to serve as an audit trail since all historic information can be quickly accessed at any time. In addition, some storage systems provide the ability to replay historical process activities so that users can easily visualize how the system has evolved over time and identify areas for improvement or investigate problems more efficiently.
Data historians are designed for scalability which helps them remain effective regardless of growth in operations size or complexity. Most systems support multiple simultaneous connections from various applications both onsite and remotely as well as local archive storage for quick retrieval when needed. The ability to connect disparate systems also makes integration with analytics platforms like Machine Learning easier so that organizations can take advantage of insights derived from their historical process data more efficiently than ever before. Moreover, many modern solutions offer features like cloud deployment along with user-friendly real-time dashboards and alerting capabilities which provide deep visibility into operations without having to sift through raw datasets manually on a regular basis.
Data historians are an essential tool for organizations to keep track of and analyze their data. Without a data historian, companies may lack the ability to accurately measure the performance or success of their operations.
Data historians allow businesses to store large amounts of historical data in a single place, which can be easily accessed and analyzed when needed. With this stored information, companies can pinpoint trends that are important to understand their current business environment. This allows them to make more informed decisions on how best to serve their customers or how they should plan for the future.
Data historians also enable companies to quickly look up past records that are necessary for making decisions about operations management and production concerns. Data historians help businesses determine what products were successful in what time period, as well as any factors that influenced those sales, such as seasonality or promotional activity from competitors. These records provide insight into where improvements need to be made; this helps ensure that processes are working efficiently without relying solely on intuition or guesswork.
Overall, data historians play an invaluable role in helping businesses thrive by providing accurate records and insights into analyzing past performance so they can improve operations planning and make changes accordingly in order to remain competitive in today's ever-changing marketplaces
The cost of data historians can vary depending on a number of factors and configurations, so it is difficult to provide an exact answer. Generally speaking, the cost for a comprehensive data historian suite can range from tens of thousands of dollars for basic packages up to several hundred thousand dollars or higher for more complex enterprise-level offerings. The best way to determine the cost associated with implementing a data historian solution is to work with an experienced vendor who can configure a package that meets your specific needs and budget.
The key features, quantity and quality of sensors, type of hardware required and complexity of analytic capabilities desired all play a role in determining the ultimate price tag for purchasing a data historian package. For example, if you’re looking for real-time alerts based on advanced analytics powered by machine learning algorithms, the price will likely be higher than if you simply needed to store time-series measurements from various sensors around your facility. It’s also important to consider whether you have existing hardware that could be leveraged as part of the installation or if new equipment must be purchased as well.
In summary, there is no single answer when it comes to determining the exact cost associated with implementing a data historian solution as every project has its own unique set of requirements that must be taken into account. However, companies should investigate vendors carefully before making any purchase decisions in order to ensure they are getting the most bang for their buck while meeting their organization's specific objectives.
Data historians can integrate with a wide range of different types of software. This includes enterprise resource planning (ERP) software, which is typically used for activities such as accounting and customer relationship management, as well as operational technology (OT) related applications that manage physical assets such as sensors and controllers. Additionally, data historians can be integrated with process control systems like SCADA or EMI/RDSI to collect real-time data from devices in the field. Business intelligence tools such as Business Objects, QlikView and Tableau can also be integrated with data historians to provide insights into historical performance for advanced analytics analysis. Finally, presentation layer tools like dashboards are often integrated so users can have a graphical representation of their datasets.