DataMatch Enterprise API
DME exposes all of its features through its API, which allows you to use any data quality management function in your custom or existing application and set it up for real-time data profiling, cleansing, matching, or deduplication.
Certified for Security, Quality, Compliance & Code Integrity.
How it works
How the DataMatch Enterprise API Works
Use cases
See how our customers use DME API
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Data governance
DME API is extensively used to automate business rules that ensure clean and high-quality data across databases at all times. The API acts as a data quality firewall between virtually any database and data entry form, and automates operations such as, transforming letter cases, rejecting certain domain email addresses, flagging potential matches and duplicates, as well as handling high confidence match results through merge purge actions. Moreover, with DME API, you can configure to trigger these operations at chosen events, for example, when a record is added or updated. This makes DME API a deduplication API and entity resolution API in one — matching and merging records across systems, not just flagging duplicates within one.
Data processing & appending
Organizations store and maintain tons of historical data records about customers and their transactions. Millions of such records are generated daily or weekly. But before new records can be moved to the core data warehouse, it must be tested for appropriate data quality standards, and in the case of duplicates, it must be matched to ensure that the upcoming record enriches the old one, and is not created again as a new record.
This is where DME API performs exceptionally well – processing large quantities of data in near real-time to pull its unique ID, performing data matching to identify exact or fuzzy matches, and appending new data attributes to the existing record.
Results accuracy
DME Performance on a dataset of 2M records
Features
What do you get with DME API?
High performance
Exceptionally high performance and scalability features, allowing tons of data to be cleansed, matched and processed on demand.
Quick implementation
Simply download and deploy the application within minutes with the help of our guided installation wizard and start matching.
Intuitive interface
A highly visual and intuitive interface made for business users, IT specialists, data analysts and scientists, as well as novice users.
Robust matching technology
Rated faster and more accurate than IBM and SAS, DME consistently had the least number of false positives in independent studies.
Seamless integration
Readily integrate the world’s fastest and most accurate data quality features into your custom-built or third-party applications.
Real time syncs
Compute exact, fuzzy, and intelligent matches in real-time, across and within multiple data sources at blazing speeds.
Solution
One solution for all data quality problems
Quick data profiling
Master record selection
Workflow orchestration
Advanced filtering
Instant and live data preview
Record Linkage and Deduplication
Phone number standardization
Bulk cleansing and standardization
Email address cleansing
Seamless data integration
Cross-column matching
Pattern matching and recognition
Customer Stories
See what our customers say...
It’s not just the software which works very well for us, but the focus and knowledge that Data Ladder brings to the table
Thanks to Data Ladder we successfully cleaned up and matched our internal sales file with new leads, greatly improving efficiency and sales.
We could not do these reports before. Now, DataMatch has become a main staple in my suite of tools that I work with
Want to know more?
Check out DME resources
Merging Data from Multiple Sources – Challenges and Solutions
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9 Best Fuzzy Matching Software for Data Teams in 2026
Last Updated on July 7, 2026 Fuzzy matching software identifies records that likely refer to the same real world entity even when the text doesn’t
Post-Merger Customer Deduplication for Two Customer Databases Without Losing Data Integrity
Last Updated on July 3, 2026 When two companies merge, their customer databases merge in name only. The same customer often exists under different account
9 Best Fuzzy Matching Software for Data Teams in 2026
Last Updated on July 7, 2026 Fuzzy matching software identifies records that likely refer to the same real world entity even when the text doesn’t
Post-Merger Customer Deduplication for Two Customer Databases Without Losing Data Integrity
Last Updated on July 3, 2026 When two companies merge, their customer databases merge in name only. The same customer often exists under different account
Data Deduplication API vs Batch Deduplication: When to Use Each
Last Updated on June 30, 2026 The right choice between a deduplication API and batch deduplication comes down to when deduplication needs to happen. If
Frequently asked questions
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