Melissa Data Quality vs Qlik Talend Cloud comparison

Melissa and Qlik are both solutions in the Data Quality category. Melissa is ranked #7, while Qlik is ranked #2 with an average rating of 8.0. Melissa holds a 4.6% mindshare in DQ, compared to Qlik’s 7.0% mindshare. Additionally, 95% of Melissa users are willing to recommend the solution, compared to 88% of Qlik users who would recommend it.

Melissa Data Quality

Read 40 Melissa Data Quality reviews

1,518 Views
1,047 Comparison Views

95% willing to recommend

Qlik Talend Cloud

Read 55 Qlik Talend Cloud reviews

8,555 Views
1,711 Comparison Views

88% willing to recommend

Melissa Data Quality

Qlik Talend Cloud

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 22, 2026

Qlik Talend Cloud and Melissa Data Quality compete in the data integration and data quality sectors. Qlik Talend Cloud has the advantage in pricing and support, while Melissa offers superior features for its price.

Features: Qlik Talend Cloud enhances integration between platforms, streamlines data transformation, and supports scalability and flexibility. Melissa Data Quality excels in data verification and enhancement, specializing in address cleansing, data matching, and deduplication.

Room for Improvement: Qlik Talend Cloud could benefit from enhanced data quality verification tools, additional configuration options for advanced data cleansing, and improved offline functionality during network outages. Melissa Data Quality requires better integration with third-party platforms, more flexible pricing models to accommodate varying budget constraints, and enhancements in user interface for a more intuitive experience.

Ease of Deployment and Customer Service: Qlik Talend Cloud offers a straightforward deployment model with robust customer support and comprehensive documentation. Melissa Data Quality emphasizes dedicated customer service, providing personalized support options and effective deployment solutions.

Pricing and ROI: Qlik Talend Cloud delivers competitive pricing with flexible models, which often result in faster ROI through efficient integration and support. Melissa Data Quality, while possibly more expensive initially, offers long-term cost-effectiveness via precision-focused features that enhance data accuracy and provide significant ROI.

To learn more, read our detailed Melissa Data Quality vs. Qlik Talend Cloud Report (Updated: March 2026).

Buyer's Guide

Melissa Data Quality vs. Qlik Talend Cloud

March 2026

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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

Melissa Data Quality

Ranking in Data Quality

7th

Ranking in Data Scrubbing Software

5th

Average Rating

8.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Qlik Talend Cloud

Ranking in Data Quality

2nd

Ranking in Data Scrubbing Software

1st

Average Rating

8.0

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Data Integration (5th), Master Data Management (MDM) Software (3rd), Cloud Data Integration (7th), Data Governance (8th), Cloud Master Data Management (MDM) (4th), Streaming Analytics (8th), Integration Platform as a Service (iPaaS) (6th)

Mindshare comparison

As of March 2026, in the Data Quality category, the mindshare of Melissa Data Quality is 4.6%, up from 2.6% compared to the previous year. The mindshare of Qlik Talend Cloud is 7.0%, down from 10.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Mindshare Distribution
Product	Mindshare (%)
Qlik Talend Cloud	7.0%
Melissa Data Quality	4.6%
Other	88.4%

Data Quality

Featured Reviews

GaryM

Data Architect at World Vision

SSIS MatchUp Component is Amazing

- Scalability is a limitation as it is single threaded. You can bypass this limitation by partitioning your data (say by alphabetic ranges) into multiple dataflows but even within a single dataflow the tool starts to really bog down if you are doing survivorship on a lot of columns. It's just very old technology written that's starting to show its age since it's been fundamentally the same for many years. To stay relavent they will need to replace it with either ADF or SSIS-IR compliant version. - Licensing could be greatly simplified. As soon as a license expires (which is specific to each server) the product stops functioning without prior notice and requires a new license by contacting the vendor. And updating the license is overly complicated. - The tool needs to provide resizable forms/windows like all other SSIS windows. Vendor claims its an SSIS limitation but that isn't true since pretty much all SSIS components are resizable except theirs! This is just an annoyance but needless impact on productivity when developing new data flows. - The tool needs to provide for incremental matching using the MatchUp for SSIS tool (they provide this for other solutions such as standalone tool and MatchUp web service). We had to code our own incremental logic to work around this. - Tool needs ability to sort mapped columns in the GUI when using advanced survivorship (only allowed when not using column-level survivorship). - It should provide an option for a procedural language (such as C# or VB) for survivor-ship expressions rather than relying on SSIS expression language. - It should provide a more sophisticated ability to concatenate groups of data fields into common blocks of data for advanced survivor-ship prioritization (we do most of this in SQL prior to feeding the data to the tool). - It should provide the ability to only do survivor-ship with no matching (matching is currently required when running data through the tool). - Tool should provide a component similar to BDD to enable the ability to split into multiple thread matches based on data partitions for matching and survivor-ship rather than requiring custom coding a parallel capable solution. We broke down customer data by first letter of last name into ranges of last names so we could run parallel data flows. - Documentation needs to be provided that is specific to MatchUp for SSIS. Most of their wiki pages were written for the web service API MatchUp Object rather than the SSIS component. - They need to update their wiki site documentation as much of it is not kept current. Its also very very basic offering very little in terms of guidelines. For example, the tool is single-threaded so getting great performance requires running multiple parallel data flows or BDD in a data flow which you can figure out on your own but many SSIS practitioners aren't familiar with those techniques. - The tool can hang or crash on rare occasions for unknown reason. Restarting the package resolves the problem. I suspect they have something to do with running on VM (vendor doesn't recommend running on VM) but have no evidence to support it. When it crashes it creates dump file with just vague message saying the executable stopped running.

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Herivao Jus Winny

IT Consultant at a tech services company with 201-500 employees

Has automated recurring data flows and improved accuracy in reporting

The best features of Talend Data Integration are its rich set of components that let you connect to almost any data design intuitive and its strong automation and scheduling capabilities. The TMap component is especially valuable because it allows flexible transformation, joins, and filtering in a single place. I also rely a lot on context variables to manage different environments like Dev, Test, and production, without changing the code. The error handling and logging tools are very helpful for monitoring and troubleshooting, which makes the workflow more reliable. Talend Data Integration has helped our company by automating and standardizing data processes. Before, many of these tasks were done manually, which took more time and often led to errors. With Talend Data Integration, we built automated pipelines that extract, clean, and load data consistently. This not only saves hours of manual effort, but also improves the accuracy and reliability of data. As a result, business teams had faster access to trustworthy information for reporting and decision making, which directly improved efficiency and productivity. Talend Data Integration has had a measurable impact on our organization. By automating daily data loading processes, we reduced manual effort by around three or four hours per day, which saved roughly 60 to 80 hours per month. We also improved data accuracy. Error rates dropped by more than 70% because validation rules were built into the jobs. In addition, reporting teams now receive fresh data at least 50% faster, which means they can make decisions earlier and with more confidence. Overall, Talend Data Integration has increased both efficiency and reliability in our data workflows.

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Quotes from Members

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

Pros

"NCOA processing is now quick and easy. No waiting for the list to come back, no calling, and no worrying if there are enough credits available."

"It cuts down significantly on time in trying to match names to addresses. I can do in a few hours what would otherwise take days to accomplish."

"We use a Melissa API to access the data, so it easy to use, accurate, and fast."

"Standardizing allows me to more effectively check for duplicate/existing records. Verifying increases the value of the data."

"By using Melissa Data, we are able to scrub and verify, then better validate the end customer's address to ensure a more consistent delivery of products."

"It has a straightforward, easy setup."

"Trial subscriptions (via cloud) are very cheap and easy to use."

"Since we switched to Melissa Data web services, we do not need to maintain those servers and/or software, and we get the most up-to-date addresses from USPS."

More Melissa Data Quality pros

"Some of the algorithms that are inbuilt in Talend Data Quality, such as Levenshtein, are the most valuable functions for us."

"The jobs are visual and this has improved collaboration between colleagues. It’s much easier to understand a visual job than a piece of Java code."

"Overall, the management and running environment are very stable, and I would rate it an eight out of ten."

"We are able to get emails from URLs very easily using this function when others fail."

"I would definitely recommend others to implement this product as it is really helpful, easy to learn, user friendly, provides lot of enhanced features, etc."

"We can develop our own code if we do not see the functionality we need."

"The best features Qlik Talend Cloud offers include the fact that it is built on Java, which gives me the chance to customize my requirements and write my own Java code to achieve my logic."

"Talend is user-friendly and has many components and connectors, which makes it a great choice."

More Qlik Talend Cloud pros

Cons

"We are very pleased with the pricing but they need to have some good licence tracking mechanism."

"MatchUp seems to be single threaded, and limits the amount of data that can be processed automatically."

"The billing structure does not seem very accurate."

"The billing structure does not seem very accurate. We’ve had issues with miscounted batch records processed"

"Pricing model."

"Did not work as advertized. Needs better results in address parsing, as described on the website."

"Update feature"

"There are some hitches in setup, especially with the new encoding, but otherwise it’s relatively simple."

More Melissa Data Quality cons

"Including either XML or JSON in the next release would definitely be a good transformation. I'm not sure if Talend has that feature, but it's one of those requirements that we are working around and have to do some parsing of XML so this could make it easier."

"With M rows, it runs too slowly and has memory issues."

"It would be more helpful if it offered dynamic dashboards that could be directly used by clients for better analysis."

"Qlik Talend Cloud could be improved with more advanced monitoring and flexible alerts, as well as better job performance visibility."

"They don't have any AI capabilities. Talend DQ is specifically for data quality, which only has data profiling. With Talend DQ, I cannot generate any reports today, so I need an ETL tool. It provides general Excel files, or I have to create some views. If instead of buying a new tool, Talend provides a reporting capability or solution, it would be great. It will reduce the development effort for creating these kinds of reports. We also manage the infrastructure for Talend. From the licensing perspective, for cloud, they only have seat licenses where one person is tied to one license, but for on-premise, they have concurrent licenses. It would be really awesome if they can provide concurrent licenses for the cloud so that if one person is not there, somebody else can use that license. Currently, it is not possible unless a person deactivates his or her license and moves the same seat license to someone else. We are one of the biggest customers in the central zone of the US for Talend, and this is the feedback that we have provided them again and again, but they come back and say that they aren't able to provide concurrent licenses on the cloud. In version 7.3, there is a feature for tokenization and de-tokenization of data. This is the feature that we are looking for. It is useful if somebody wants to see what we have masked and how do we demask it. This feature is not there in version 7.1. There are also a few other capabilities on the cloud, but we don't yet have a big footprint in the cloud."

"There are more functions in a non-streamlined manner, which could be refined to arrive at a better off-the-shelf functions."

"Processing large volumes of data sometimes consumes a lot of resources."

"Qlik Talend Cloud is doing well, but one improvement could be the integration of development functionalities we use in Talend Studio directly onto the Talend browser."

More Qlik Talend Cloud cons

Pricing and Cost Advice

"We are concerned that our own pricing is going up every year for Melissa Data products, but we highly recommend the services for people who are routinely sending out mailings."

"The price for address validation is similar in all software. However, the price for geocoding decides the actual pricing. If you get their most accurate geocoding (called GeoPoints), then it will add about $10k+ per million requests."

"Trial subscriptions (via cloud) are very cheap and easy to use. It’s a great way to test Listware to see if you want to go deeper with integration."

"It is affordable."

"Understand how may transactions you will be processing so that you can get the right tier pricing."

"You should have a good idea of the size of your data and the amount of cleansing you will be doing, so you will purchase the appropriate size bundle."

"Buy a lot more credits than you think you’re going to need."

"Pricing is very reasonable."

More Melissa Data Quality pricing and cost advice

"The solution's pricing is very reasonable and half the cost of Informatica."

"The pricing is a little higher than what I had expected, but it's comparable with I-PASS competitors."

"The price of the Talend Data Management Platform is reasonable. The other competing solutions are priced high. Gartner Magic Quadrant identified other solutions, such as Informatica, that are far more expensive."

"The licensing cost is about 40,000 Euros a year."

"The product pricing is considered very good, especially compared to other data integration tools in the market."

"License renewal is on a yearly basis."

"It's a subscription-based platform, we renew it every year."

"The tool is cheap."

More Qlik Talend Cloud pricing and cost advice

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Top Industries

By visitors reading reviews

Insurance Company

13%

Computer Software Company

Manufacturing Company

Educational Organization

Financial Services Firm

13%

Computer Software Company

10%

Comms Service Provider

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	3
Large Enterprise	14

By reviewers
Company Size	Count
Small Business	20
Midsize Enterprise	11
Large Enterprise	20

Questions from the Community

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Earn 20 points

What needs improvement with Talend Data Quality?

I don't use the automated rule management feature in Talend Data Quality that much, so I cannot provide much feedback. I may not know what Talend Data Quality can improve for data quality. I'm not ...

See all answers

What is your primary use case for Talend Data Quality?

It is for consistency, mainly; data consistency and data quality are our main use cases for the product. Data consistency is the primary purpose we use it for, as we have written rules in Talend Da...

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What advice do you have for others considering Talend Data Quality?

Currently, I'm working with batch jobs and don't perform real-time data quality monitoring because of the large data volume. For real-time, we use a different product. I cannot provide details abou...

See all answers

Comparisons

Experian Data Quality vs Melissa Data Quality

Compared 16% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Melissa Data Quality

Compared 7% of the time

Coheris Spad Data Quality vs Melissa Data Quality

Compared 5% of the time

BCC Data Quality vs Melissa Data Quality

Compared 5% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 4% of the time

More Melissa Data Quality Competitors

Informatica Intelligent Data Management Cloud (IDMC) vs Qlik Talend Cloud

Compared 5% of the time

SSIS vs Qlik Talend Cloud

Compared 3% of the time

n8n vs Qlik Talend Cloud

Compared 2% of the time

Databricks vs Qlik Talend Cloud

Compared 2% of the time

Collibra Platform vs Qlik Talend Cloud

Compared 2% of the time

More Qlik Talend Cloud Competitors

Product Reports

Buyer's Guide

Melissa Data Quality

March 2026

Download Melissa Data Quality product report

Buyer's Guide

Qlik Talend Cloud

March 2026

Download Qlik Talend Cloud product report

Also Known As

No data available

Talend Data Quality, Talend Data Management Platform, Talend MDM Platform, Talend Data Streams, Talend Data Integration, Talend Data Integrity and Data Governance

Overview

Data Quality Components for SSIS

This suite of data transformations for Microsoft SQL Server Integration Services (SSIS) delivers the full spectrum of data quality including data profiling, data verification, data enrichment and data matching. With an intuitive interface and drag/drop capabilities, this powerful toolkit makes it easy to unify data into a single version of the truth for Master Data Management (MDM) success.

Melissa

Qlik Talend Cloud provides robust data integration tools tailored for efficient management of large volumes, offering real-time data access, Java integration, and custom code capabilities for developers.

Qlik Talend Cloud is known for its extensive connectivity options, enabling seamless integration across different platforms, such as S3, Redshift, Oracle, and SQL Server. The central repository facilitates consistent metadata access throughout organizations, enhancing collaboration. Despite its strengths in advanced monitoring, automation, and user-friendly drag-and-drop interfaces, users face challenges with installation stability, technical support, documentation inconsistencies, and complexities in learning. Performance concerns also include multitasking limitations and excessive memory usage. The platform's licensing costs can be prohibitive for smaller companies, while demands for improved data governance and intuitive code management continue. Its applications in healthcare data parsing, ETL task automation, and diverse data platform integration demonstrate its utility, although there's a constant demand for better scalability and efficient transformations.

What are the key features?

Seamless Real-Time Data Access: Ensures that users can access the latest information across systems without delays for better decision-making.
Java Integration: Facilitates smooth incorporation of Java components into workflows, broadening development options.
Custom Code Development: Offers flexibility to develop tailored solutions to meet specific integration scenarios.
Vast Connectors: Enhances connectivity between multiple platforms, supporting comprehensive data integration strategies.
Central Repository: Allows for uniform metadata access across departments, promoting cohesive data management practices.
Automation and Monitoring: Streamlines workflows with advanced automation and monitoring, reducing manual intervention and errors.

What benefits and ROI should users evaluate?

Improved Data Quality: Tools for data matching and error handling ensure high-quality, reliable data for analytics and reporting.
Efficient Workflow Streamlining: Drag-and-drop interfaces and automation features simplify complex workflows, enhancing operational efficiency.
Enhanced Business Insights: By integrating diverse data sources, businesses can derive deeper insights and ensure compliance through better data management.
Cost Management: Although some users find licensing expensive, comprehensive feature sets aimed at improving data processes can justify costs.
Community Support: Users benefit from active community forums that provide assistance, although technical support also necessitates enhancements.

In specialized industries like healthcare, users leverage Qlik Talend Cloud for data integration and transformation, aiding in compliance and analytics. Compatibility with cloud and on-premises systems ensures adaptability to complex data tasks, facilitating business application development. Organizations focus on enhanced data ingestion and quality checks for comprehensive solutions.

Qlik

Sample Customers

Boeing Co., FedEx, Ford Motor Co, Hewlett Packard, Meade-Johnson, Microsoft, Panasonic, Proctor & Gamble, SAAB Cars USA, Sony, Walt Disney, Weight Watchers, and Intel.

Aliaxis, Electrocomponents, M¾NCHENER VEREIN, The Sunset Group

Buyer's Guide

Melissa Data Quality vs. Qlik Talend Cloud

March 2026

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