Melissa Data Quality Scalability

GM
Data Architect at World Vision

We can run 9 million customer record exact matches in 10 minutes using 5 partitions/parallel dataflows. Survivorship takes another 50 minutes. I'm sure you could run faster with dedicated hardware and running more parallel dataflows. The tool starts to exponentially slow down once you pass about 2 million customers in a single dataflow so its best to keep it at or under that number although mileage will vary depending on the complexity of your matching.  Its unfortunate that the vendor hasn't built in parallelism which would both eliminate the need to do this yourself.  They should be able to auto-scale it based on # of CPU's your running.

Even with that limitation this tool is magnitudes faster than the last matching tool I used and it wasn't a simple plug-in to an ETL tool. I recently heard of a competing tool that takes longer to match just a few thousand customers than this tool takes to run millions of them.

Note:

We probably run higher volumes than many organizations. For B2B and daily matching you could probably process a delta in a matter of a few minutes with this tool.  

Note:  I suspect an essential ingredient when considering scalability is whether you're calling a web service for matching or just on-prem. Their SSIS component is only on-prem but they offer a web service as well which we have not tested.

Combining survivorship and matching in the same data flow slows performance. We got much better performance by running in two separate dataflows - the first for just matching and then another for just survivorship (re-using the previous grouping numbers in the first match) to make it perform to our requirements.

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SV
Powerbuilder Consultant at a government with 10,001+ employees

No issues. In fact, we have increased our request volume in the last three years and they have been able to accommodate us easily and smoothly.

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it_user798219 - PeerSpot reviewer
General Manager
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Data Quality
March 2024
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it_user503892 - PeerSpot reviewer
Senior Project Manager at a retailer with 1,001-5,000 employees

We had found a bug that only appeared when trying to match over 94,000 records. The process hung and we could not identify without a lot of testing what was going on. Their support team worked with me to determine the issue.

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DP
IT Director

No issues. We do a very high volume of traffic in a condensed window during the September-October-November timeframe, and we have never had an issue with performance or scalability. 

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it_user796209 - PeerSpot reviewer
CS Operations Manager

No scalability issues at all.

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GG
COO

No scalability issues.

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it_user798222 - PeerSpot reviewer
Head of Data Partnerships at a tech services company with 11-50 employees

No issues with scalability.

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it_user793638 - PeerSpot reviewer
Property Investor

I haven't seen any problems yet. I do have to go through White Pages to try and get information about an owner, which is a different set. I'd love to see that incorporated in Melissa Data.

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it_user496830 - PeerSpot reviewer
Information Technology Leader at a healthcare company with 1,001-5,000 employees
RW
CTO at a comms service provider with 11-50 employees

Have not tested, but sure the calls can be scaled.

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it_user790491 - PeerSpot reviewer
Director, Information Technology at a financial services firm with 10,001+ employees
it_user796218 - PeerSpot reviewer
Developer at a tech services company with 1-10 employees

Larger batches sometimes have failed batches.

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it_user150288 - PeerSpot reviewer
Technical Lead/Solution Architect at a insurance company with 10,001+ employees

We didn't encounter issues

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it_user796212 - PeerSpot reviewer
Customer Resource Production Manager at a individual & family service with 5,001-10,000 employees

Not applicable.

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it_user223296 - PeerSpot reviewer
Applied Data Science Entrepreneur at a consultancy with 1-10 employees

It depends on whether you can run extremely large lists on multiple servers. Any sort of dedupe or fuzzy match is processing intensive, regardless of the vendor.

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it_user793653 - PeerSpot reviewer
Administrative Assistant
it_user798009 - PeerSpot reviewer
Operations and Business Technology Leader at a financial services firm with 10,001+ employees

No scalability issues.

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it_user793635 - PeerSpot reviewer
President

It has good capability. It probably has about as good a capability as what it's ever going to have.

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it_user498804 - PeerSpot reviewer
Software Solutions Architect at a real estate/law firm with 501-1,000 employees
it_user798006 - PeerSpot reviewer
Director at a logistics company with 1,001-5,000 employees

No scalability issues.

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it_user793617 - PeerSpot reviewer
Director of Platform Operations at a tech services company with 51-200 employees
it_user793656 - PeerSpot reviewer
Executive Director at a non-tech company with 11-50 employees
it_user791220 - PeerSpot reviewer
Office Services Manager at a government with 51-200 employees
it_user790494 - PeerSpot reviewer
Director of Software Development
it_user467340 - PeerSpot reviewer
Owner /CEO at a consultancy with 501-1,000 employees

It has been able to scale for our needs.

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it_user791217 - PeerSpot reviewer
Business Intelligence Developer at a healthcare company with 1,001-5,000 employees
it_user793650 - PeerSpot reviewer
Manager of Application Development (Web Team) at a retailer with 1,001-5,000 employees
it_user796215 - PeerSpot reviewer
Mailing Specialist

No scalability issues.

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WK
Director at a tech services company with 1-10 employees
it_user793629 - PeerSpot reviewer
Product Design Consultant

We did not encounter any issues.

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it_user793659 - PeerSpot reviewer
Data Processing Supervisor at a printing company with 51-200 employees
it_user793614 - PeerSpot reviewer
Works at a tech company with 51-200 employees
it_user793620 - PeerSpot reviewer
President at a tech company with 51-200 employees
it_user793623 - PeerSpot reviewer
Data Solutions at a tech company with 51-200 employees

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

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Buyer's Guide
Data Quality
March 2024
Find out what your peers are saying about Melissa, Informatica, Experian and others in Data Quality. Updated: March 2024.
765,234 professionals have used our research since 2012.