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

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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

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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.

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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

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

"Helps our organization provide accurate address information to our customers for direct mailing (household) and other campaigns they want to do."

"There have been tangible benefits in combating fraudulent transactions. The information from Melissa Data is fed straight into our fraud system. This creates efficiency but also removes the need for manual address checks."

"This tool works better for us than using a batch processing system that we do not have enough control over as each record is being processed."

"It has a straightforward, easy setup."

"It gives me an assessed value of the property in question. My partner and I are property investors, and it's good to get an assessed value to cull out properties that we're not interested in."

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

"By validating and parsing the addresses our customers submit to us, we have reduced the number of addressing errors encountered during our processing."

More Melissa Data Quality pros

"The product's integration with PostgreSQL and Jira has been helpful for us. Its performance is good. However, we do not use it for large data sets."

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

"The best feature of Talend Data Integration is its multiple data DB components; we have almost all the components and also cloud versions, with TMC allowing us to perform data preparation and data stewardship."

"The solution is customizable."

"Talend's most valuable feature is its ability to generate code and packages efficiently."

"This product speeds up the unit testing and QA for specific test scenarios. As a result, the development output quality can be evaluated and adjusted."

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

"The Studio is easy to understand."

More Qlik Talend Cloud pros

Cons

"The SSIS component setup seems a little klunky."

"Needs more/better search tools are needed. Also, state and local tax data would be nice."

"We are no longer using Melissa Data to clean up our address information as there are free tools that we can use to do the same thing."

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

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

"Pricing is based on tiers, with each tier capped at a specified number of records processed. Once you go over the cap at one tier, you are automatically bumped to the next tier. However, they seem to count failed batch processes so it’s good to keep track of the number of records sent. They’ll fix the count when notified, but their system fails to detect actual successful processes versus failed processes."

"More countries should be supported by Melissa."

"Address validation and parsing in a few countries have room for improvement."

More Melissa Data Quality cons

"The solution's memory sometimes bottlenecks and that can be challenging."

"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."

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

"The product must enhance the data quality."

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

"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 tool's technical support needs to be better. It doesn't have a local data center but pushes everything to the cloud. They need to check in with customers to see if they're happy and how well the solutions work. They need to assign a customer success manager for the accounts they sell."

"Finding assistance with issues can be spotty. With Python, there are literally millions of open source answers which are recent and apply to the version that we are using."

More Qlik Talend Cloud cons

Pricing and Cost Advice

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

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

"Pricing is very reasonable, no licensing required."

"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."

"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."

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

"Depends on situation. We prefer to have data onsite, but some might prefer web access."

"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."

More Melissa Data Quality pricing and cost advice

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

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

"The tool is cheap."

"It is cheaper than Informatica. Talend Data Quality costs somewhere between $10,000 to $12,000 per year for a seat license. It would cost around $20,000 per year for a concurrent license. It is the same for the whole big data solution, which comes with Talend DI, Talend DQ, and TDM."

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

"License renewal is on a yearly basis."

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

More Qlik Talend Cloud pricing and cost advice

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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...

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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...

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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

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