> For the complete documentation index, see [llms.txt](https://docs.zingg.ai/0.5.0/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zingg.ai/0.5.0/stepbystep/relations.md).

# Combining Different Match Models

When a single match model is not sufficient

[Zingg Enterprise Feature](#user-content-fn-1)[^1]

In many cases, we want to build the identity graph using a combination of different datasets, schemas and matching logic. An example could be having a source system which only contains userids and emails, another one wtih user name and phone numbers and a few others with person information with addresses. Another example could be some systems capturing spousal information, but others to be matched on the basis of lastname and address.

In such cases, Zingg can build the entire graph and relate different models together. In the following case, results of a query with exact match on family Id and a matching model(household) using address and lastname are brought together.

````json
```
{ 
    "vertices" : 
    [ 
        { 
            "name" : "spouse",  
            "vertexType" : "zingg_pipe", 
            "data" : [
                {
                "name" : "spouse", 
                "format" : "snowflake", 
                "props": {
                        "query": "select a.id as id, a.FNAME, a.LNAME, a.STNO, a.ADD1, a.CITY, a.STATE, a.ZINGG_ID_PERSON, b.id as z_id, b.fname as Z_FNAME,b.lname as Z_LNAME,b.stno as Z_STNO,b.add1 as Z_ADD1, b.city as Z_CITY,b.state as Z_STATE, b.ZINGG_ID_PERSON as Z_ZINGG_ID_PERSON from CUSTOMER_RELATE_PARTIAL a, CUSTOMER_RELATE_PARTIAL b where a.familyId = b.familyId"
                        }
                }
                ],
            "edges" :  
            {   "edgeType" : "same_edge",
                "edges":[
                    {
                        "dataColumn" : "zingg_personId",
                        "column" : "zingg_personId",
                        "name" : "zingg_personId1"
                    },
                    {
                        "dataColumn" : "zingg_personId",
                        "column" : "z_zingg_personId",
                        "name" : "zingg_personId2"
                    }
                ]
            }
        },
        { 
            "name" : "household",
            "config" : "$ZINGG_ENTERPRISE_HOME$/zinggEnterprise/configHousehold.json", 
            "strategy" : {
                "vDataStrategy" : "unique_edge",
                "props" : {
                        "column" : "zingg_personId",
                        "edge" : "zingg_personId,z_zingg_personId"
                    }
            },
            "vertexType" : "zingg_match", 
             "edges" :  
            {   "edgeType" : "same_edge",
                "edges":[
                    {
                        "dataColumn" : "zingg_personId",
                        "column" : "zingg_personId",
                        "name" : "zingg_personId1"
                    },
                    {
                        "dataColumn" : "zingg_personId",
                        "column" : "z_zingg_personId",
                        "name" : "zingg_personId2"
                    }
                ]
            }
        }
    ],
    "output" : [{
        "name":"relatedCustomers", 
        "format":"snowflake", 
        "props": {
            "table": "RELATED_CUSTOMERS_PARTIAL"
            }
    }],
    "strategy":"pairs_and_vertices"
}


```
````

[^1]: Zingg Enterprise is an advance version of Zingg Community with production grade features


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