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Informatica Intelligent Data Management Cloud (IDMC) vs Upsolver comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Mar 15, 2026

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

Informatica Intelligent Dat...
Ranking in Data Integration
1st
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
215
Ranking in other categories
Data Quality (1st), Business Process Management (BPM) (5th), Business-to-Business Middleware (1st), API Management (9th), Cloud Data Integration (3rd), Data Governance (3rd), Test Data Management (2nd), Cloud Master Data Management (MDM) (1st), Data Management Platforms (DMP) (2nd), Data Masking (2nd), Metadata Management (2nd), Integration Platform as a Service (iPaaS) (5th), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd), AI Data Analysis (1st)
Upsolver
Ranking in Data Integration
40th
Average Rating
8.6
Reviews Sentiment
7.6
Number of Reviews
4
Ranking in other categories
Streaming Analytics (22nd)
 

Mindshare comparison

As of October 2026, in the Data Integration category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 3.8%, down from 4.2% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Informatica Intelligent Data Management Cloud (IDMC)3.8%
Upsolver0.7%
Other95.5%
Data Integration
 

Featured Reviews

RC
Contractor at Sanlam
Cloud data catalog has streamlined lineage and quality while leaving more automation to improve
I have not explored IDMC's automation capabilities driven by AI and metadata too much at the moment, but it is on the cards. We are basically creating the foundation, as the whole migration has taken place recently and it is still early days. I think Informatica Intelligent Data Management Cloud (IDMC) is evolving, and as the vendors move forward, they pick up new concepts from each other. I have seen that products leapfrog each other, and from my experience over the years, the big players tend to copy features or add enhancements based on industry trends. I feel whatever the tool does not have now, there is a feedback loop allowing us to request new features, and we continually ask for different ways to do things as we have a pipeline into the product management team. It is difficult to say what additional features I would prefer to see in the next release of IDMC. I would appreciate more automation on the lineage front, with more AI to seamlessly join independent sources and create seamless lineage between different technologies, such as from file into database A into a different database and landing up in a reporting system such as Cognos, Qlik, Qlik Sense, QlikView, or Power BI.
reviewer2784462 - PeerSpot reviewer
Software Engineer at a tech vendor with 10,001+ employees
Streaming pipelines have become simpler and onboarding new data sources is now much faster
One of the best features Upsolver offers is the automatic schema evolution. Another good feature is SQL-based streaming transformations. Complex streaming transformations such as cleansing, deduplication, and enrichment were implemented using SQL and drastically reduced the need for custom Spark code. My experience with the SQL-based streaming transformations in Upsolver is that it had a significant positive impact on the overall data engineering workflow. By replacing custom Spark streaming jobs with declarative SQL logic, I simplified development, review, and deployment processes. Data transformations such as parsing, filtering, enrichment, and deduplication could be implemented and modified quickly without rebuilding or redeploying complex code-based pipelines. Upsolver has impacted my organization positively because it brings many benefits. The first one is faster onboarding of new data sources. Another one is more reliable streaming pipelines. Another one is near-real-time data availability, which is very important for us. It also reduced operational effort for data engineering teams. A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days. Custom Spark code reduction reached 50 to 40 percent. Pipeline failures are reduced by 70 to 80 percent. Data latency is improved from hours to minutes.

Quotes from Members

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

Pros

"It allows the creation of identical tasks that can be applied across multiple tables, ranging from 100 to even 1,000 tables."
"The feature I found most valuable in Informatica Intelligent Cloud Services is the mapping. You just drag, and it maps the data. Mapping is very easy, and it's no code. When you migrate data or when the data interaction happens at the source and destination, the challenge is that you'll get different formats. The validation has to be done in the middleware, and the transformation should happen. In Informatica Intelligent Cloud Services, it's very easy to do data validation and transformation compared to any other tool."
"It comes with lot of features and is a one-stop-shop solution for integration, data modeling, and data governance. Everything can be built under one particular umbrella. If any issues come up, then there won't be any blame game saying that it could be an integration issue or an MDM hub issue because it's wholly owned by Informatica. That's the biggest advantage of Informatica MDM over that of any other tools that are available on the market."
"The solution provides increased efficiency while still being user-friendly and easy to operate."
"The connectivity and their whole suite are valuable features because whether we need data cleansing or data mastering, we get it all in one platform and there's no need to test different cloud vendors and then integrate with one solution since Informatica is a one-stop shop."
"The solution has multiple valuable features for metadata collection"
"The most important features are the mastering of the data and the UI intuitiveness."
"We use parts and standardization for most of our testing. We purchase the US Postal Service address database, which is updated periodically. Many useful tools, such as Google Maps, can detect and mark new businesses or changes in business locations. Informatica captures and updates this information. Some periodic maintenance is involved, but setting it up is not overly complicated."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
"I have saved 50 to 60% on maintaining pipelines since using Upsolver."
"A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days, custom Spark code reduction reached 50 to 40 percent, pipeline failures are reduced by 70 to 80 percent, and data latency is improved from hours to minutes."
 

Cons

"Its pricing model can be improved."
"I have encountered some issues using the substitution, which is one of the techniques of data masking."
"Informatica Axon needs more integration connectors so that it can connect to systems and different kinds of datasets."
"One area that could use improvement is the speed of the web interfaces. At present, they are very slow. I think it is essential that we are original and robust on-premises."
"Its cloud-based version has a few limitations compared to the on-premise version."
"Connectivity could be improved, it can be a little slow."
"The GUI needs to be a little more user-friendly and appealing."
"We experienced several basic issues with the product that required daily meetings with Informatica product specialists."
"I would say Upsolver's scalability is eight out of 10 because of pricing."
"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."
"There is room for improvement in query tuning."
"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
 

Pricing and Cost Advice

"Comparatively, their prices are a little bit too high."
"We switched to Informatica PIM because it was cheaper than the Oracle solution. It is cheaper initially, but they will bundle it later. This is what happens in the industry."
"The pricing is quite flexible."
"I have heard from customers that the product comes with a huge license cost."
"We saw an ROI. We have been able to get data from various sources and consolidate it into a data lake, which is helping us in data analytics."
"A yearly subscription is paid based on the number of people using the solution. Price-wise, it falls under the medium range since it is neither very costly nor too cheap."
"The pricing model is something that can be improved."
"You pay for this solution based on IPUs, Informatica Processing Units. This depends on how much data you process and how much memory you consume from the cloud provider, and you pay as you go."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
10%
Outsourcing Company
9%
Construction Company
9%
Real Estate/Law Firm
14%
Manufacturing Company
14%
Retailer
12%
Outsourcing Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business51
Midsize Enterprise27
Large Enterprise155
No data available
 

Questions from the Community

How does Azure Data Factory compare with Informatica Cloud Data Integration?
Azure Data Factory is a solid product offering many transformation functions; It has pre-load and post-load transformations, allowing users to apply transformations either in code by using Power Q...
Which Informatica product would you choose - PowerCenter or Cloud Data Integration?
Complex transformations can easily be achieved using PowerCenter, which has all the features and tools to establish a real data governance strategy. Additionally, PowerCenter is able to manage huge...
What are the biggest benefits of using Informatica Cloud Data Integration?
When it comes to cloud data integration, this solution can provide you with multiple benefits, including: Overhead reduction by integrating data on any cloud in various ways Effective integration ...
What is your experience regarding pricing and costs for Upsolver?
My experience with pricing, setup cost, and licensing is that the pricing is nine out of 10.
What needs improvement with Upsolver?
I think Upsolver can be improved with deeper integration with external orchestration out of the box. I would appreciate more clear dashboards with billing in real time as a needed improvement.
What is your primary use case for Upsolver?
My main use case for Upsolver is to operate with changes in the structure of new data without a pipeline disrupting. I write SQL queries in Upsolver, and the platform takes care of the data itself,...
 

Also Known As

ActiveVOS, Active Endpoints, Address Verification, Persistent Data Masking
No data available
 

Overview

 

Sample Customers

The Travel Company, Carbonite
Information Not Available
Find out what your peers are saying about Informatica Intelligent Data Management Cloud (IDMC) vs. Upsolver and other solutions. Updated: September 2026.
917,403 professionals have used our research since 2012.