When selecting a destination, it’s important to first verify that all the data sources you want to connect to Stitch will be compatible.
As Stitch currently allows only one destination per account, we recommend verifying your integrations’ compatibility before connecting a destination. This will ensure that you can successfully connect and replicate data from all your sources.
Degrees of Incompatibility
The compatibility of any integration/destination combination falls into one of three categories: always compatible, sometimes compatible, and never compatible.
The matrices below use the following icons to indicate the degree of incompatibility for an integration/destination combo:
- indicates that, as far as we know, this combo is always compatible.
- indicates that this combo is sometimes compatibile - there may be compatibility issues, but they’re infrequent.
- indicates that this combo is never compatible. It’s unlikely that Stitch will be able to load data from this integration into the given destination.
Incompatible Integrations by Destination Type
Below you’ll find a list of integrations that may have full or partial incompatibility with any of Stitch’s destination offerings.
BigQuery
For a comprehensive look at how BigQuery will load data - including what may cause data to be "rejected" - refer to the BigQuery Data Loading Guide.
| Integration | Level | Reason for Incompatibility |
| Mixpanel |
Mixpanel sometimes sends records that contain multiple data types. BigQuery only allows FLOAT and DOUBLE data types in the same column; otherwise, the field will be rejected.
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| Segment |
Segment sometimes sends records that contain multiple data types. BigQuery only allows FLOAT and DOUBLE data types in the same column; otherwise, the field will be rejected.
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| Shopify |
Shopify sometimes sends records that contain multiple data types. BigQuery only allows FLOAT and DOUBLE data types in the same column; otherwise, the field will be rejected.
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| Zendesk |
Zendesk sometimes sends records that contain multiple data types. BigQuery only allows FLOAT and DOUBLE data types in the same column; otherwise, the field will be rejected.
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Panoply
For a comprehensive look at how Panoply will load data - including what may cause data to be "rejected" - refer to the Panoply Data Loading Guide.
| Integration | Level | Reason for Incompatibility |
| MongoDB | As a result of the de-nesting Stitch performs on nested structures, deeply nested data in Mongo may result in tables that exceed Panoply’s 1,600 column limit. |
PostgreSQL
For a comprehensive look at how PostgreSQL will load data - including what may cause data to be "rejected" - refer to the PostgreSQL Data Loading Guide.
| Integration | Level | Reason for Incompatibility |
| Facebook Ads | Tables created as a result of de-nesting nested data will have names that exceed PostgreSQL’s limit of 59 characters. PostgreSQL data warehouses will always reject these tables as a whole, meaning Stitch will be unable to load them. |
Redshift
For a comprehensive look at how Redshift will load data - including what may cause data to be "rejected" - refer to the Redshift Data Loading Guide.
| Integration | Level | Reason for Incompatibility |
| MongoDB | As a result of the de-nesting Stitch performs on nested structures, deeply nested data in Mongo may result in tables that exceed Panoply’s 1,600 column limit. |
Full Destination/Integration Compatibility Matrix
For a comprehensive look at the compatibility of all Stitch's integrations and destinations, check out the matrix below.
| Related | Troubleshooting |
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