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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 June 2026, in the Data and Analytics Service Providers category, the mindshare of Fabric Data is 0.7%, up from 0.7% compared to the previous year. The mindshare of Seeq is 1.4%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data and Analytics Service Providers Mindshare Distribution
ProductMindshare (%)
Seeq1.4%
Fabric Data0.7%
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

"I have seen a return on investment that is highly notable; the solutions I am getting from transitioning traditional ETL solutions to Fabric Data are remarkable."
"Fabric Data has positively impacted my organization by decreasing the storage-level cost, and we now have different teams, including a data analytics team and a data engineering team, all on one platform, allowing us to directly check the data analytics part."
"The unified workspace is the biggest advantage I experienced while building those data pipelines and working with OneLake storage."
"Fabric Data has positively impacted my organization as my company is a consultant company and we have implemented these projects for our clients."
"Fabric Data has allowed us to change that and put the entire solution in one package and one environment, and that also makes things much more stable."
"Fabric Data offers the best features by delivering a well-integrated, modern data engineering experience as a learning and certification platform."
"Fabric Data has positively impacted our organization as it has been our go-to tool for data integration with the help of Microsoft services."
"We have certainly saved a significant amount of time by switching from small-scale tools to Fabric Data, which has improved visibility and increased accuracy."
"My advice to other professionals considering implementing Seeq is that they should definitely go for it, because among the tools on the market, it is very easy to integrate, easy to scale, and easy to visualize in different environments."
"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."
"Seeq is a friendly and useful tool."
"AI is great in Seeq. You have a good feature that allows you to convert a Python algorithm built in Seeq Data Lab into a user-friendly interface."
"I love how easy Seeq is to use and how quickly you can build an analysis."
"The solution's most valuable feature is the prediction model."
"Seeq only needed me to complete the task, so it saved other people's time, and it saved my time by being easy to use and thereby also saving money."
"This resulted in a net savings of approximately one million dollars of extra product per year."
 

Cons

"One area is performance optimization and monitoring visibility for large-scale workloads."
"I believe Excel sheets have some issues when creating a data frame; however, JSON data works fine for Fabric Data. When using an Excel sheet, we need some extra libraries, and that feature would be useful because most e-commerce sites store data in Excel."
"Fabric Data can be improved because it tends to be run by Fabric Capacity, which is basically the compute cycles, and it is not very clear on how and what that is going to be used."
"The main improvement I would like to see is more integration with other tools; for example, SAP integration should be there because there are more integration tools available in Azure Data Factory than in Fabric Data, and I would like to have more integrations in Fabric Data."
"I felt some features, particularly around the Dataflow Gen2 error handling and pipeline monitoring, lacked clear documentation at the time of my study."
"To improve Fabric Data, I suggest more integration with additional data sources and better integration for data agents."
"One thing regarding needed improvements is related to the free tier or trial capacity. When I was learning Microsoft Azure services, it was very easy to get credits and a free account, but in Fabric, it was inconvenient to get a free tier or trial capacity."
"I think Fabric Data could be improved by adding more notebooks, even though it currently has one."
"I would like to test the software for free for a longer time."
"Regarding AI, I wish Seeq had AI capabilities. For instance, if Seeq could analyze graphs and offer recommendations, it would be advantageous. Currently, there is no AI feature in Seeq. In terms of improvements, it would be great if Seeq could enhance its data export features and possibly integrate more functionalities to reduce the need for multiple software tools. I would like a specific feature related to predictive analysis, which Seeq currently lacks."
"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."
"In Seeq Organizer, we've realized that process engineers want dashboards with more drag-and-drop features, like Power BI."
"Seeq could work on the reporting format and dashboard."
"I appreciate the question on how Seeq can be improved. The first thing is their graphical user interface. They invest so much in their backbone, but without a good dashboard or visualization tool, it feels insufficient."
"We face a bit of an issue if there are any server issues or upgrades from Seeq."
"The technical support services need improvement."
 

Pricing and Cost Advice

Information not available
"The pricing is average."
"The solution's pricing is comparable to other products."
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Top Industries

By visitors reading reviews
Manufacturing Company
18%
Financial Services Firm
16%
University
14%
Healthcare Company
9%
Manufacturing Company
28%
Energy/Utilities Company
11%
Construction Company
9%
Healthcare 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...
 

Comparisons

No data available
 

Overview

Find out what your peers are saying about Fabric Data vs. Seeq and other solutions. Updated: June 2026.
900,644 professionals have used our research since 2012.