Splink
6.2#16 in data deduplication softwareFree planFree planLinuxSelf-hosted
VisitSplink vs Zingg
What both publish
| Fact | Splink | Zingg |
|---|---|---|
| Matching | It supports term frequency adjustments and user-defined fuzzy matching logic. | It combines machine learning matching with rule based deterministic matching, which can use identifiers such as email, SSN, and passport ID. |
| Matching features | It supports term-frequency adjustments and user-defined fuzzy-matching logic. | The feature set includes nickname mappings, company-name dictionaries, multilingual matching, stop words and categorical standardization. |
| Purpose | Splink is a Python package for probabilistic record linkage that deduplicates and links records without unique identifiers. | Zingg is open source, warehouse native master data management software for resolving entities and building unified views from siloed data. |
| Scale | Linkage jobs can run with DuckDB or big-data backends such as Spark for 100+ million records. | The comparison page lists support for millions of records across Community, Enterprise Lite and Enterprise editions. |
| Support | The documentation directs users with questions to the project’s GitHub discussion forum. | The comparison page lists open source support for Community and enterprise grade support for both Enterprise editions. |
Splink plans
- SplinkFree
Zingg plans
- CommunityFree
- Community (Open Source)Free
- EnterprisePriced on request
- Enterprise LitePriced on request
- Zingg EnterprisePriced on request
- Zingg Enterprise LitePriced on request
Pick Splink if…
Splink suits Python users who need to link or deduplicate records without unique identifiers, especially where records have several standardised fields. It may fit work in government, academia, or the private sector where the documented backends meet the deployment needs.
Pick Zingg if…
You want what its maker publishes above — check its page for the details.