DataMatch Enterprise vs dedupe
DataMatch Enterprise
dataladder.comdedupe
github.comSide by side
| Figure | DataMatch Enterprise | dedupe |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 0 |
| Spec score · Data Deduplication Software | 8.8 (#1) | 7.9 (#12) |
| Headquarters | 68 Bridge St Suite 307, Suffield, CT 06078, United States | Chicago, Illinois, United States |
| Intended users | The maker describes its visual interface as intended for business users, IT specialists, data analysts and scientists, and novice users. | The maintainers describe the library as suitable for integration into applications or import scripts, while the former Dedupe.io service was designed as an online tool for non-developers. |
| Support | The product page lists [email protected] and +1 (888) 779 6578 as contact details. | The library documentation directs bug reports to GitHub Issues and lists a mailing list for users. |
| What it does | DataMatch Enterprise is a code-free toolkit for importing, profiling, cleansing, matching, deduplicating, merging and exporting data. | The dedupe Python library uses machine learning for fuzzy matching, deduplication, and entity resolution on structured data. |
Plans
DataMatch Enterprise
- DataMatch EnterprisePriced on request
- DataMatch Enterprise + Address VerificationPriced on request
- DataMatch Enterprise + APIPriced on request
In their own words
DataMatch Enterprise
DataMatch Enterprise is a code-free toolkit for profiling, cleansing, matching, and deduplicating data from multiple sources. Its profiling tools identify quality problems and help surface where data may need cleansing, standardization, matching, or deduplication. Matching methods include phonetic, numeric, domain-specific, and fuzzy approaches, with adjustable algorithm levels and weights. An address module verifies and corrects mailing addresses, fills missing details, and adds ZIP+4 geocoding information. A REST API makes cleansing and matching functions available to custom projects. The containerized release can run on Linux, on-premises infrastructure, or in the cloud; listed platforms also include web and Windows. Visual entity graphs support review of matched groups from a particular run, rather than persistent identity graphs across batches. The maker describes the interface as intended for business users, IT specialists, data analysts and scientists, and novice users. The product is paid, with pricing on request; a free trial is available, but there is no free plan.