Melissa Data Quality vs Qlik Talend Cloud comparison

Melissa and Qlik are both solutions in the Data Quality category. Melissa is ranked #5 with an average rating of 9.0, while Qlik is ranked #2 with an average rating of 8.0. Melissa holds a 4.4% 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

1,315 Views
894 Comparison Views

95% willing to recommend

Qlik Talend Cloud

Read 55 Qlik Talend Cloud reviews

7,726 Views
1,545 Comparison Views

88% willing to recommend

Melissa Data Quality

Qlik Talend Cloud

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Nov 18, 2025

Qlik Talend Cloud and Melissa Data Quality compete in the data management category, each offering distinct features that cater to specific business needs. Qlik Talend Cloud holds an edge in terms of pricing and support, while Melissa Data Quality is preferred for its powerful features despite higher costs.

Features: Qlik Talend Cloud offers integration capabilities, data transformation tools, and a robust set of components for handling various workflows. In contrast, Melissa Data Quality provides advanced data cleansing, address verification, and geocoding features, focusing on data integrity and accuracy.

Room for Improvement: Qlik Talend Cloud could benefit from enhanced data accuracy tools, better address verification features, and improved cleansing options. Melissa Data Quality might improve its cost structure, provide more competitive pricing, and offer enhanced integration capabilities to broaden its appeal.

Ease of Deployment and Customer Service: Qlik Talend Cloud supports multiple environments, allowing easy integration into existing systems, with reliable customer service. Melissa Data Quality ensures straightforward deployment with specialized support for complex data issues, benefiting those needing in-depth assistance.

Pricing and ROI: Qlik Talend Cloud is more budget-friendly, appealing to businesses focused on ROI by offering effective data manipulation at a lower cost. Melissa Data Quality requires a higher initial investment but provides substantial ROI through precise data enrichment features, justifying its premium price with long-term value.

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

Buyer's Guide

Melissa Data Quality vs. Qlik Talend Cloud

February 2026

Download the complete report

Helped 881,733 peers since 2012

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

5th

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 (6th), 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) (8th)

Mindshare comparison

As of February 2026, in the Data Quality category, the mindshare of Melissa Data Quality is 4.4%, up from 2.6% compared to the previous year. The mindshare of Qlik Talend Cloud is 7.0%, down from 10.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Quality Market Share Distribution
Product	Market Share (%)
Qlik Talend Cloud	7.0%
Melissa Data Quality	4.4%
Other	88.6%

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.

Read full review

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.

Read full review

Quotes from Members

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

Pros

"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."

"The high value in this tool is its relatively low cost, ease of use, tight integration with SSIS, superior performance (compared to competitors), and attribute-level advanced survivor-ship logic."

"Initial setup was fairly straightforward. The documentation was very good in terms of how to integrate and consume the service(s) that we use. It did not take an abundance of time to set up things on our side to use the service."

"SSIS integration."

"I was able to dedupe millions of records in the past, and append the most recent email."

"We only use the one feature for the NAICS code. This allows our product users to know what industry a business is in."

"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."

"The customers' addresses are now complete, correct and follow one consistent format."

More Melissa Data Quality pros

"The solution can run on any machine and that is a big advantage."

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

"It offers advanced features that allow you to create custom patterns and use regular expressions to identify data issues."

"The most valuable feature is the data loading and scripting language"

"It is saving a lot of time. Today, we can mask around a hundred million records in 10 minutes. Masking is one of the key pieces that is used heavily by the business and IT folks. Normally in the software development life cycle, before you project anything into the production environment, you have to test it in the test environment to make sure that when the data goes into production, it works, but these are all production files. For example, we acquired a new company or a new state for which we're going to do the entire back office, which is related to claims processing, payments, and member enrollment every year. If you get the production data and process it again, it becomes a compliance issue. Therefore, for any migrations that are happening, we have developed a new capability called pattern masking. This feature looks at those files, masks that information, and processes it through the system. With this, there is no PHI and PII element, and there is data integrity across different systems. It has seamless integration with different databases. It has components using which you can easily integrate with different databases on the cloud or on-premise. It is a drag and drop kind of tool. Instead of writing a lot of Java code or SQL queries, you can just drag and drop things. It is all very pictorial. It easily tells you where the job is failing. So, you can just go quickly and figure out why it is happening and then fix it."

"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."

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

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

More Qlik Talend Cloud pros

Cons

"There are some companies out there using Google or other sources to check / confirm if addresses are residential. If Melissa is not doing this, that could be an improvement."

"Speed of delivery/ease of use. They advertise a 24-hour, next business day turn time on data annotation, but I’ve found it is usually closer to 72 hours. This is still excellent, just make sure you add in the appropriate fluff to your delivery timelines."

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

"We encounter failed batch processes once in a while, but their team is quick to rectify issues."

"One of the problems that we ran into this year was we probably spent over 40 hours finding and trying to drill down to where specific bugs were in the program, which was a tremendous waste of time for us. There were a couple of updates to Windows this year, the program kept crashing. It happened on two different occasions over a period of a few months. Once we told them what the problem was - even though their tech support is great to work with - it literally took probably about two months to fix the issue where we could actually use the program the way we needed to use it."

"It would be nice if it also had a user interface, as it did in years past."

"The SSIS component setup seems a little klunky."

"I wish there was a way to do a "test run" and see what a particular format will give you."

More Melissa Data Quality cons

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

"Needs integrated data governance in terms of dictionaries, glossaries, data lineage, and impact analysis. It also needs operationalization of meta-data."

"The product must enhance the data quality."

"I think they should drive toward AI and machine learning. They could include a machine-learning algorithm for the deduplication."

"There are too many functions which could be streamlined."

"I would like to sync a project and do an upload from that current version, and then from GitLab, be able to download the latest one."

"The ability to change the code when debugging the JavaScript could be improved."

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

More Qlik Talend Cloud cons

Pricing and Cost Advice

"It's affordable."

"Cloud version is very cheap. On-premise version is expensive."

"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."

"Generally, the cost is ROI positive, depending on your shipping volume."

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

"This vendor has no equal in pricing for equivalent functionality."

"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."

"They were willing to work with our preferred vendors, though it involved extra steps to get the license."

More Melissa Data Quality pricing and cost advice

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

"The price is on a per-user basis. It's a little more expensive than other tools. There aren't any additional costs beyond the standard licensing fee."

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

"I would advise to first take a look and at the Open Studio edition. Figure out what you need and purchase the appropriate license."

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

"Moreover, the pricing structure stands out as highly competitive compared to other offerings in the market, making it a cost-effective choice for users."

"We did not purchase a separate license for DQ. It is part of our data platform suite, and I believe it is well-priced."

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

More Qlik Talend Cloud pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Data Quality solutions are best for your needs.

See recommendations

881,733 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Insurance Company

15%

Educational Organization

Manufacturing Company

Computer Software Company

Financial Services Firm

13%

Computer Software Company

10%

Comms Service Provider

Manufacturing Company

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

Ask a question

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...

See all answers

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 14% of the time

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

Compared 8% of the time

Coheris Spad Data Quality vs Melissa Data Quality

Compared 7% of the time

Anchor Software Data Quality vs Melissa Data Quality

Compared 6% of the time

Ataccama ONE Platform 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 7% of the time

SSIS vs Qlik Talend Cloud

Compared 3% of the time

Collibra Platform vs Qlik Talend Cloud

Compared 2% of the time

n8n vs Qlik Talend Cloud

Compared 2% of the time

Databricks vs Qlik Talend Cloud

Compared 2% of the time

More Qlik Talend Cloud Competitors

Product Reports

Buyer's Guide

Melissa Data Quality

January 2026

Download Melissa Data Quality product report

Buyer's Guide

Qlik Talend Cloud

January 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

February 2026

Free Report: Melissa Data Quality vs. Qlik Talend Cloud

Find out what your peers are saying about Melissa Data Quality vs. Qlik Talend Cloud and other solutions. Updated: February 2026.

DOWNLOAD NOW

881,733 professionals have used our research since 2012.

See our Melissa Data Quality vs. Qlik Talend Cloud report.

See our list of best Data Quality vendors, best Data Scrubbing Software vendors, and best Cloud Data Integration vendors.

We monitor all Data Quality reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.