Why Zingg

How Zingg Compares

The biggest difference is where matching runs. Hosted or self-hosted, every option that loads your records into its own store adds pipelines to build, a second copy to secure, and sync to keep running. Zingg matches your tables where they already are.

ZinggBuild It YourselfMDM HubsInformatica, Reltio, Tamr, CluedInEntity Resolution EnginesSenzing, Tilores, QuantexaCustomer Data PlatformsAmperity
Where your data livesStays in your warehouse or lakehouseIn your platformCopied into the hub, in the vendor's cloud or yoursLoaded into the engine's own store, as SaaS or self-hostedIngested into the CDP, with some zero-copy options
Cost of moving dataNone. No pipelines out, no second copyNoneETL into the hub, a second copy, sync backPipelines into the engine and a second copy to keep in sync, even when self-hostedIngestion pipelines and a second copy of customer data
Matching approachLearned from 40–50 labelled pairs, plus deterministic rules in EnterpriseHand-written rules that breakConfigured match rules, with AI assistancePre-tuned engines or configured rulesCustomer identity rules plus scoring
Blocking and scaleLearned from your labelled pairs, so there are no blocking rules to design or retuneYou design blocking and retune it as data grows, or comparisons explodeVaries; some, like Tamr, ask you to define and tune blocking termsVaries by engineHandled inside the product
EntitiesAny entityWhatever you build forSeveral master data domainsMostly people and organisationsCustomers and households
Time to first resultsDays. Label 40–50 pairsMonths of rules and tuningLong implementation projectsQuick to start, then integrate into your appsSet up around marketing sources and activation
OpennessOpen source core, inspectableYours to maintainProprietaryProprietaryProprietary