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Informatica Intelligent Data Management Cloud (IDMC) vs Syniti Data Quality comparison

 

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 Quality
1st
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
215
Ranking in other categories
Data Integration (1st), Business Process Management (BPM) (6th), Business-to-Business Middleware (2nd), API Management (7th), 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) (3rd), Test Data Management Services (3rd), Product Information Management (PIM) (1st), Data Observability (2nd), AI Data Analysis (1st)
Syniti Data Quality
Ranking in Data Quality
19th
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Data Quality category, the mindshare of Informatica Intelligent Data Management Cloud (IDMC) is 9.7%, down from 18.6% compared to the previous year. The mindshare of Syniti Data Quality is 2.7%, down from 9.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Quality Mindshare Distribution
ProductMindshare (%)
Informatica Intelligent Data Management Cloud (IDMC)9.7%
Syniti Data Quality2.7%
Other87.6%
Data Quality
 

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.
RA
Delivery Head at ApikinFotech
Offers predefined rules and easy to migrate data with minimum customisation of rules
The customization of the data needs improvement. We need to build basic SQL queries rather than being able to do it within the tool. We need to be able to analyze the SQL queries and then rerun them based on customer usage. We should be able to tune the existing process by using simple SQL queries based on the customer's requirements. In future releases, I would like to see more features around Preload and postload reports. From the end-user point of view, it is not very feasible to read. I need to know how the data has been migrated. I need to know whether the complete data has been migrated, only the required data has been migrated, and how it was migrated. So the postload reports will give validation between the source data and the target source. It would give exact picture of the data migration.

Quotes from Members

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

Pros

"Single and consistent view of Customer Data arising from a centralized data set with unique customer records."
"It has become an easy way to exchange information through any cloud application."
"It is quite easy to use and flexible."
"The process of using the tool's scalability option is well documented."
"I rate the solution's scalability a ten out of ten."
"The data mapping capability is a valuable feature."
"The way that the solution scans is very useful."
"The ability to clean out data and improve the data quality is the best feature."
"Syniti has built-in 80% of the solution, and we only need to customize 20 to 25% of the features. It is easy to run and pre-load reports."
"The major benefits of Syniti Data Quality stem from the productivity and flexibility it offers to users."
"The customer service and support is good."
"With Syniti Data Quality, you can integrate SAP and directly fix errors from Syniti Data Quality instead of logging into SAP and then fixing them."
 

Cons

"They could provide more robust performance for data integration processes. It would help in improving the data quality more efficiently."
"The licenses are too expensive compared to before, which is why customers are now preferring other data metadata management tools like OneTrust, Collibra, and Azure Purview."
"The product requires more polishing and hardening."
"With limited data it's fine, but with a large volume the scalability is questionable, the threshold of data transaction is different."
"When we compared Informatica to SAP, we realized that we lose the ability to integrate easily with our SAP business applications"
"It is more complicated to extract data using the product compared to Visio. The system could display the details on the screen."
"Informatica Axon needs to improve its interface."
"The data discovery isn't that good yet for Salesforce. We have another tool that we use for this. It may be a problem because Salesforce on the cloud."
"The customization of the data needs improvement. We need to build basic SQL queries rather than being able to do it within the tool. We need to be able to analyze the SQL queries and then rerun them based on customer usage."
"The loading mechanisms and administration processes, particularly in setting up connections and deploying the system, need improvement."
"It would be good if Syniti Data Quality could integrate more AI in the future."
"In Syniti Data Quality, data extraction is an area with certain shortcomings where improvements are required."
 

Pricing and Cost Advice

"I rate the product's pricing a five on a scale of one to ten, where one is cheap and ten is expensive."
"The product is not very pocket-friendly for small and medium-sized businesses, and it is understandable because of the kind of features the tool gives."
"I have heard from customers that the product comes with a huge license cost."
"Informatica Cloud Data Quality is a costly solution."
"The solution is expensive."
"Informatica MDM's price could be lower."
"We are quite happy with the licensing model."
"Licensing is difficult to understand, but the team is always available to explain anything. They are very helpful."
"The solution is expensive."
"I would rate the pricing a six out of ten, where one is cheap, and ten is expensive."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
10%
Construction Company
9%
Outsourcing Company
6%
Manufacturing Company
15%
Retailer
8%
University
7%
Government
6%
 

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

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Also Known As

ActiveVOS, Active Endpoints, Address Verification, Persistent Data Masking
Syniti DQ
 

Overview

 

Sample Customers

The Travel Company, Carbonite
Kraft Foods, Puget Sound Energy
Find out what your peers are saying about Informatica Intelligent Data Management Cloud (IDMC) vs. Syniti Data Quality and other solutions. Updated: August 2026.
908,834 professionals have used our research since 2012.