dataPARC Historian

dataPARC Historian

dataPARC
5.0 out of 5 stars
Foghub dataPARC Historian

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Foghub:

About

Simplified IT/OT Integration, Data Engineering & Real-Time Edge Intelligence. Easy to use, cross-platform, open architecture, edge computing for industrial time-series data. Foghub offers the Critical-Path to IT/OT convergence, connecting Operations (Sensors, Devices, and Systems) with Business (People, Processes, and Applications), enabling automated data acquisition, data engineering, transformations, advanced analytics and ML. Handle large variety, volume, and velocity of industrial data with out-of-the-box support for all data types, most popular industrial network protocols, OT/lab systems, and databases. Easily automate the collection of data about your production runs, batches, parts, cycle-times, process parameters, asset condition, performance, health, utilities, consumables as well as operators and their performance. Designed for scale, Foghub offers a comprehensive set of capabilities to handle large volumes and velocity of data.
dataPARC Historian:

About

Get better performance from your time-series data with the dataPARC Historian, an enterprise-grade solution designed to elevate industrial data operations to new heights. The dataPARC Historian simplifies complex data sharing, ensuring seamless collaboration across departments with enhanced security and performance. Its compatibility with external AI, ML, and cloud applications via an open architecture increases adaptability and strategic insights. Experience rapid data access, enriched manufacturing intelligence, and a platform that grows with your business needs. dataPARC historian is the smart choice for enterprises aiming for the forefront of operational excellence. The dataPARC historian is more than a data historian; it's a gateway to unlocking greater flexibility and efficiency in leveraging your time-series data. It's crafted for those who demand reliability, speed, and intuitive use, making every data interaction impactful.
Foghub:

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
dataPARC Historian:

Platforms Supported

Windows Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported
Foghub:

Audience

Companies and anyone requiring a platform designed for simplified IT/OT integration, data engineering and real-time edge intelligence
dataPARC Historian:

Audience

Manufacturing plants
Foghub:

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported
dataPARC Historian:

Support

Phone Support Supported
24/7 Live Support Supported
Online Supported
Foghub:

API

Offers API Not Supported
dataPARC Historian:

API

Offers API Supported
Foghub:

Screenshots and Videos

dataPARC Historian:

Screenshots and Videos

Foghub:

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported
dataPARC Historian:

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported
Foghub:

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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dataPARC Historian:

Reviews/Ratings

Overall 5.0 / 5
ease 4.5 / 5
features 5.0 / 5
design 5.0 / 5
support 4.5 / 5
dataPARC Historian:

Pros & Cons from Real Users

Pros

  • Ease of use, stability, the platform offers the best HMI experience of all other products in the industry.
  • Quick, easily accessible, and visually clear data presentation. Easy enough to use that operators often already have trends built and tags pulled when troubleshooting before I ever get to the control room. Alarming and reporting functionality is very useful, other historian packages seem to require separate software packages to handle the alarm/reporting side of things, it is nice to have it all in one package. I really like the parc calc server option, it is a great way to handle complex data manipulation in real time and allows us to take large amounts of data and refine it down to be more presentable for KPI sheets and daily scorecards.
  • I like the speed for data retrieval as well as the ability to historize calculated tags. I also like the PARCdata interface that allows me to craft SQL queries for data retrieval. I've also been successful with a proof-of-concept using python OPC to retrieve historical data from their UA server. With the technical matching or superiority compared to competitors, the significantly lower price makes the decision obvious.

Cons

  • It’s challenging to pull MDE tags and sort by grade
  • Biggest struggle has been integrating the software into a network with changing IT security practices. The data collectors live on the process network and operators are accessing it from a business network there is a bit of management that must take place to ensure connectivity while also maintaining security. This would be an issue with any historian system, but because of the depth of deployment, the number of functions we rely on dataPARC for, and the amount of data we pass between the networks, any change in permissions or restrictions on the network can limit operability of the software suite. With other data historian systems since their functionality is more constrained, network issues don't reach as far.
  • Really, the only aspect of the historian that I struggle with is the security console. It allows me to achieve what I need regarding security, but the learning curve was unexpected steep for me.
Foghub:

Training

Documentation Not Supported
Webinars Not Supported
Live Online Supported
In Person Supported
dataPARC Historian:

Training

Documentation Supported
Webinars Supported
Live Online Supported
In Person Supported
Foghub:

Company Information

Foghub
Founded: 2019
United States
www.foghub.io
dataPARC Historian:

Company Information

dataPARC
Founded: 1997
United States
www.dataparc.com
Foghub:

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dataPARC Historian:

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dataPARC Historian:
Foghub:

Categories

Data Engineering Supported
IoT Analytics Supported
dataPARC Historian:

Categories

Data Analysis Supported
Data Historians Supported
Data Visualization Supported
Industrial IoT Supported
IoT Analytics Supported
Manufacturing Supported
OEE Supported
Foghub:

Integrations

AVEVA PI System Not Supported
Amazon Web Services (AWS) Supported
App Orchid Not Supported
Braincube Not Supported
Google Analytics Supported
Google Cloud Platform Supported
Hadoop Supported
Ignition SCADA Not Supported
Microsoft Azure Supported
Ndustrial Contxt Not Supported
PARCview Not Supported
PI Vision Not Supported
PreCognize Not Supported
Proficy Smart Factory MES Not Supported
RtDUET Not Supported
Seeq Not Supported
TrendMiner Not Supported
Uptake Not Supported
Visual KPI Not Supported
WhatsApp Supported
dataPARC Historian:

Integrations

AVEVA PI System Supported
Amazon Web Services (AWS) Not Supported
App Orchid Supported
Braincube Supported
Google Analytics Not Supported
Google Cloud Platform Not Supported
Hadoop Not Supported
Ignition SCADA Supported
Microsoft Azure Not Supported
Ndustrial Contxt Supported
PARCview Supported
PI Vision Supported
PreCognize Supported
Proficy Smart Factory MES Supported
RtDUET Supported
Seeq Supported
TrendMiner Supported
Uptake Supported
Visual KPI Supported
WhatsApp Not Supported
Foghub:
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