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Fabric Data vs Seeq comparison

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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 September 2026, in the Data and Analytics Service Providers category, the mindshare of Fabric Data is 0.9%, up from 0.4% compared to the previous year. The mindshare of Seeq is 1.5%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data and Analytics Service Providers Mindshare Distribution
ProductMindshare (%)
Seeq1.5%
Fabric Data0.9%
Other97.6%
Data and Analytics Service Providers
 

Featured Reviews

XW
Student at Northeastern University
Unified data workflows have simplified certification prep and improved hands-on analytics practice
The unified workspace is the biggest advantage I experienced while building those data pipelines and working with OneLake storage. Having data ingestion, transformation, storage, and reporting all within one platform significantly reduces the complexity of switching between tools. The integration with the broader Microsoft ecosystem felt natural, especially for someone who is already familiar with Azure services. The Microsoft Learn documentation and sandbox environments made it accessible for structured self-study. Fabric Data's strongest aspect positively impacts my organization and my work with its native integration across the Microsoft data stack. OneLake serves as a single unified storage layer across all Fabric Data workloads, meaning data written by a pipeline is immediately accessible in Lakehouse, Warehouse, and Power BI without duplication or manual transfer. This eliminates the data silo problem that commonly affects multi-tool environments. Dataflow Gen2 uses the familiar Power Query interface, making it accessible to analysts already working in Excel or Power BI. The output of a dataflow can be directly directed into a Lakehouse table, which then becomes queryable via the SQL analytics endpoint without additional configuration, significantly impacting my workflow.
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

"What I appreciate about Fabric Data is that it is easy to use and user-friendly, and additionally, it is cost-efficient."
"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."
"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."
"The unified workspace is the biggest advantage I experienced while building those data pipelines and working with OneLake storage."
"The best features are that the entire ecosystem is inside Microsoft and it is under a SaaS platform."
"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."
"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."
"The best features Fabric Data offers are its versatility, as you can use data fabric for many uses in one single platform."
"Compared to any other platform, Seeq is the best and most adaptive."
"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."
"The predictive analytics features have been instrumental in catching excursions early, allowing us to monitor conditions proactively and prevent issues from escalating."
"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."
"This resulted in a net savings of approximately one million dollars of extra product per year."
"Of course, when data is processed correctly, all three outcomes—saving time, reducing downtime, and improving efficiency—are achievable."
"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."
"Seeq has impacted our organization positively because now with Seeq training, we are able to put it out to more people."
 

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."
"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."
"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."
"I have observed some limitations with Fabric Data, especially when it comes to bringing data from private networks."
"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."
"Speed is a factor which Fabric Data says and confirms they will improve. The data speed will improve, but it is not a significant improvement as per the capability of 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."
"One area is performance optimization and monitoring visibility for large-scale workloads."
"Stability issues happen multiple times because it may be the on-premise tool issue."
"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."
"Seeq could incorporate more closed-loop solutions."
"I would like to test the software for free for a longer time."
"In terms of needed improvements, for machine monitoring, we used to create our own software to conduct monitoring."
"However, the product is challenging to use given the multitude of features, and not everyone can immediately start using it, particularly on the administration side."
"The technical support services need improvement."
"I would appreciate more detailed training beyond what we received during Seeq bootcamp, which is foundational."
 

Pricing and Cost Advice

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

By visitors reading reviews
Manufacturing Company
17%
Financial Services Firm
14%
University
11%
Outsourcing Company
8%
Manufacturing Company
28%
Energy/Utilities Company
12%
Construction Company
8%
Outsourcing Company
7%
 

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: September 2026.
913,806 professionals have used our research since 2012.