No more typing reviews! Try our Samantha, our new voice AI agent.

Fabric Data vs Seeq comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Fabric Data
Ranking in Data and Analytics Service Providers
3rd
Average Rating
8.0
Number of Reviews
21
Ranking in other categories
No ranking in other categories
Seeq
Ranking in Data and Analytics Service Providers
2nd
Average Rating
8.2
Number of Reviews
26
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data and Analytics Service Providers category, the mindshare of Fabric Data is 0.8%, up from 0.5% compared to the previous year. The mindshare of Seeq is 1.3%, up from 0.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data and Analytics Service Providers Mindshare Distribution
ProductMindshare (%)
Seeq1.3%
Fabric Data0.8%
Other97.9%
Data and Analytics Service Providers
 

Featured Reviews

PV
Data Engineer at IRT Dogotal ANlytics
Automation of complex data workflows has reduced processing time and improves project delivery
The best features Fabric Data offers include Fabric Data Shortcut as the main feature, and also the integration of all the components like ingestion, transformation notebooks, and the deployment pipeline for CI/CD, which are game-changing. The visualization features are also great, and the features Fabric Data offers are different. The feature I find myself using the most is the time travel feature because I mainly work with data transformation. Whenever bad updates happen, I use the time travel feature the most. There is a high concurrency feature that can be applied in pipelines; we just need to add the high concurrency tag, and the pipeline will not start a new cluster each time the notebook runs. Fabric Data will use the same cluster for the notebook run, and this feature is a game-changer. Fabric Data positively impacts my organization by bringing us more projects and work to do and also reduces the time significantly. Nearly 20 to 30 hours per week were reduced by using Fabric Data, and it is also very cost-optimized.
Suradech Kongkiatpaiboon - PeerSpot reviewer
Senior Process Engineer at Chevron
Centralized analytics has transformed time series optimization and collaboration across teams
In my opinion, the best feature Seeq offers is the ability to visualize time series data in an efficient way. If we code it by ourselves, it will take a very long time or require a lot of server capacity, and you cannot simply plot a time series of, say, 100,000 records on your own simply because it takes a lot of effort to do that. Analyzing it when we apply any formula or algorithm takes more time to finalize everything. Seeq does this through drag and drop and point and click actions. So, it is much easier to do it by using this tool. Seeq has positively impacted my organization because I see many people using it, compared to the past five years when we had only PI Vision for visualizing time series data. Manipulating time series data was such a critical task that not many people were familiar with and were afraid to do. This task remains a core critical function for everyone to do it efficiently in order to complete anything. Process optimization and reliability analysis would address all failure modes.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Fabric Data offers several standout features that are best in class."
"I enjoy working with the pipelines since they provide a full end-to-end use case for me to take the data and report everything in one place instead of going back and forth with databases and engineers, allowing me to feel as a data scientist, data engineer, and business analyst in one location, giving me full authority to control everything."
"Fabric Data has positively impacted our organization as it has been our go-to tool for data integration with the help of Microsoft services."
"I reduced around 60% latency using Fabric Data and created one single source of truth on the Microsoft ecosystem when working with a pharmaceutical industry."
"Fabric Data has impacted my organization positively because collaboration has been better and deployments have been faster."
"What I appreciate about Fabric Data is that it is easy to use and user-friendly, and additionally, it is cost-efficient."
"Fabric Data enables me to get the data from multiple resources, whether on-premises or any other Azure service providers, and also allows me to transfer and migrate the data from any other platform to Fabric Data smoothly."
"Previously, we were using Databricks for this, but we switched to Fabric Data because Fabric Data is more integrated, we don't need to shift our data from one tool to another, and all the processing and visualization can be done inside Microsoft Fabric Data."
"Seeq has provided visibility to the key performance indicators and visualization of those critical pointers in our dashboards."
"I like Seeq because it’s very useful for production surveillance. It provides detailed insights, like the ability to view data down to the minute, which is helpful for tracking when a well goes offline. This feature is particularly beneficial for our needs. However, we don’t use Seeq for predictive analytics; we handle that with other software."
"Compared to any other platform, Seeq is the best and most adaptive."
"Seeq helps me with building those prediction models by making the process much faster, and its pre-processing capabilities are exactly what I need, making it a comprehensive platform for doing everything I need to do in data analytics."
"The initial setup is very easy. I've installed and upgraded Seeq in the remote agent service."
"This is a very simple yet powerful tool that can connect to the historian in real time, and then we can perform some formula-based calculations."
"I love how easy Seeq is to use and how quickly you can build an analysis. I've worked in the manufacturing industry for over 30 years, setting up data collection systems to record historical data. Usually, we were trending that data, which isn't very valuable. Being able actually to find value in historical data with Seeq has been great. It's quick and easy to set up monitoring and eliminate nuisance alarms. For example, process alarms typically go off mid-batch when adding materials, causing things to go out of spec. This used to create hundreds of nuisance alarms, but the tool reduces it to just the important ones."
"Seeq positively impacts my organization by enabling us to analyze significantly more data and use advanced analytic techniques that were previously reserved for programmers, opening that capability up to scientists who had no programming experience."
 

Cons

"The inability to monitor properly and having to build in fail conditions in pipelines, or navigate around it, was so painful that it is borderline unuseful for any large company in a production environment, and that would be at the top of my list."
"To improve Fabric Data, I suggest more integration with additional data sources and better integration for data agents."
"I did encounter one challenge recently in Power Query editor where I had to perform the same amount of transformations for multiple reports, repeating the transformations for each row each time."
"I felt some features, particularly around the Dataflow Gen2 error handling and pipeline monitoring, lacked clear documentation at the time of my study."
"I feel that the Copilot in Power BI is very weak; for example, if you power it with the cloud, it is much more powerful than the Copilot in Power BI, which I believe could offer much better insights since it is a Microsoft tool."
"Customer support receives a rating of six out of ten because they themselves are trying to figure out what is new and what the issue is."
"I cannot say that the analytics and reporting capabilities of Fabric Data are good enough because it only provides compatibility with Microsoft Power BI."
"I think Fabric Data could be improved by adding more notebooks, even though it currently has one."
"I think Seeq could improve by including a section that has SQL-type visualizations to visualize tables of data and not reference them to the timestamp, as that has caused us some problems at times."
"We face a bit of an issue if there are any server issues or upgrades from Seeq."
"But customers who purchase Seeq and expect its dashboarding feature to be competitive with Power BI and Grafana might be disappointed."
"Seeq could work on the reporting format and dashboard."
"However, the downsides are that it still requires a certain level of expertise to use the tools effectively, and it seems to be built for someone more devoted to the applications."
"Regarding stability, I've noticed that Seeq can sometimes be slow, even when I'm using a good Wi-Fi connection."
"I have noticed that Seeq sometimes struggles with connectivity issues, leading to data gaps."
"Sometimes the software would be a bit slow to respond, and that may be because there were too many users at once."
 

Pricing and Cost Advice

Information not available
"The solution's pricing is comparable to other products."
"The pricing is average."
report
Use our free recommendation engine to learn which Data and Analytics Service Providers solutions are best for your needs.
908,834 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Manufacturing Company
17%
Financial Services Firm
15%
University
13%
Healthcare Company
8%
Manufacturing Company
27%
Energy/Utilities Company
12%
Construction Company
8%
Outsourcing Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise2
Large Enterprise16
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise2
Large Enterprise20
 

Questions from the Community

What is your experience regarding pricing and costs for Fabric Data?
My experience with pricing, setup cost, and licensing is that pricing and those aspects are a different matter. It is not a concern for me because it matters to the client. Compared to other option...
What needs improvement with Fabric Data?
One area Fabric Data can be improved is the semantic model refresh. Though it says it is a direct link, the refresh times of the semantic model sometimes need explicit refresh. This takes a bit of ...
What is your primary use case for Fabric Data?
My main use case for Fabric Data is building data solutions for one of the retail firms in the US. I use Fabric to process source data, perform data processing, and provide analytical reports for e...
What needs improvement with Seeq?
I believe Seeq can be improved because report rollouts on similar pieces of equipment can be challenging. If Seeq had an easier way to modify our tag structure, then duplicating reports onto simila...
What is your primary use case for Seeq?
My main use case for Seeq is incident investigations. Upon unexpected quality results, incident investigations can start to determine where the incident first began occurring. Seeq allows the retro...
What advice do you have for others considering Seeq?
My advice to others looking into using Seeq is to pursue it. There are more opportunities with your own equipment than you know without examining them through the lens of Seeq. I would rate this pr...
 

Overview

Find out what your peers are saying about Fabric Data vs. Seeq and other solutions. Updated: June 2026.
908,834 professionals have used our research since 2012.