Microsoft SQL Server Data Loading Behavior

A table without a Primary Key is replicated.

• Initial job: Table is created without Primary Key and NOT NULL constraints.

• Subsequent jobs: If using Key-based Incremental or Log-based Incremental Replication, data will be added to the table in an Append-Only fashion.

  If using Full Table Replication, the table will be overwritten in its entirety during each job.

A table with a single Primary Key is replicated.

• Initial job: Table is created with Primary Key constraint. The Primary Key column has NOT NULL constraint.

• Subsequent jobs: If using Key-based Incremental or Log-based Incremental Replication, data will be de-duped based on the Primary Key column and upserted into the table.

  If using Full Table Replication, the table will be overwritten in its entirety during each job.

A table with multiple Primary Keys is replicated.

• Initial job: Table is created with Primary Key constraint. The Primary Key columns have NOT NULL constraint.

• Subsequent jobs: If using Key-based Incremental or Log-based Incremental Replication, data will be de-duped based on the Primary Key columns and upserted into the table.

  If using Full Table Replication, the table will be overwritten in its entirety during each job.

The table’s Primary Key(s) is/are changed.

An error occurs and Stitch stops processing data for the table.

The following error will display in the Notifications tab in Stitch:

1. Drop the table in Microsoft SQL Server
2. Reset the table in Stitch. This will queue a full re-replication of the table’s data, and re-create the table in Microsoft SQL Server with the correct data type for the Primary Key column.

The table’s Primary Key(s) type is/are changed.

An error occurs and Stitch stops processing data for the table.

The following error will display in the Notifications tab in Stitch:

1. Drop the table in Microsoft SQL Server
2. Reset the table in Stitch. This will queue a full re-replication of the table’s data, and re-create the table in Microsoft SQL Server with the correct data type for the Primary Key column.

The number of Primary Keys in the table is changed.

An error occurs and Stitch stops processing data for the table.

1. Drop the table in Microsoft SQL Server
2. Reset the table in Stitch. This will queue a full re-replication of the table’s data, and re-create the table in Microsoft SQL Server with the correct data type for the Primary Key column.

A table using Key-based Incremental Replication is replicated where the Replication Key column contains NULL values.

• During the initial job, the table will be created and all rows will be replicated.
• During subsequent jobs, only rows with populated Replication Keys will be replicated and persisted to Microsoft SQL Server.

A table name contains more characters than allowed by Microsoft SQL Server.

Microsoft SQL Server will reject all data for the table.

The following error will display in the Notifications tab in Stitch:

Table name [TABLE] is too long for Microsoft SQL Server

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

If possible, change the table name in the source to be less than Microsoft SQL Server’s character limit of 113 characters.

Use the _sdc_rejected table to identify the root of the issue.

A column name contains more characters than allowed by Microsoft SQL Server.

Microsoft SQL Server will reject columns with names that exceed the column character limit. Other columns in the table will persist to Microsoft SQL Server.

The following error will display in the Notifications tab in Stitch:

Column name [COLUMN] is too long for Microsoft SQL Server

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

If possible, change the column name in the source to be less than Microsoft SQL Server’s character limit of 128 characters.

Use the _sdc_rejected table to identify the root of the issue.

Two columns are replicated that canonicalize to the same name.

For example: A table containing both CustomerId and customerid columns.

Microsoft SQL Server will reject the records and create a log for the rejected records in the _sdc_rejected table in that integration’s schema.

The following error will display in the Notifications tab in Stitch:

Field collision on [COLUMN_NAME]

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

If possible, re-name one of the columns in the source so that both column names will be unique when replicated to Microsoft SQL Server.

Use the _sdc_rejected table to identify the root of the issue.

A column is replicated that has a mixed-case name.

Microsoft SQL Server will convert letters to lowercase. For example:

A column is replicated that has a name with spaces.

Microsoft SQL Server will convert spaces to underscores, with the exception of leading and trailing spaces. For example:

A column name contains leading or trailing spaces.

Microsoft SQL Server will trim leading and trailing spaces. For example:

A column is replicated with a name that contains unsupported special characters.

Microsoft SQL Server will convert special characters to underscores, with the exception of the following characters: @, $ and #. For example:

A column name starts with a special character.

Microsoft SQL Server will remove all leading special characters with the exception of leading underscores. For example:

A column name is equal to a reserved word in Microsoft SQL Server.

Microsoft SQL Server will quote column names which are reserved words. For example:

A table contains entirely NULL columns.

No table is created in Microsoft SQL Server. At least one column must have a non-NULL value for Stitch to create a table in Microsoft SQL Server.

A table arrives with more columns than Microsoft SQL Server allows.

Microsoft SQL Server will reject all data for the table.

The following error will display in the Notifications tab in Stitch:

ERROR: too many columns

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

If possible, deselect some columns to allow Stitch to load data into Microsoft SQL Server for the table. Microsoft SQL Server has a limit of 1,024 columns per table.

Use the _sdc_rejected table to identify the root of the issue.

Stitch detects multiple data types for a single column.

To accommodate data of varying types, Stitch will create multiple columns to ensure data is loaded with the correct type. In the destination, this will look like the column has been “split”.

For example: Stitch first detected that order_confirmed contained BOOLEAN data, but during a subsequent job, detected STRING values. To accommodate data of varying types, Stitch will:

1. Store data for the original data type in the original column. In this example, only BOOLEAN values will be stored in order_confirmed. The name of the original column will not change.

2. Create additional columns to store the other data types - one for each data type detected - and append the data type to the column name. In this example, a order_confirmed__st column will be created to store STRING values.

Data is replicated to Microsoft SQL Server that is nested, containing many top-level properties and potentially nested sub-properties.

Nested data will be maintained.

If the data contains nested arrays, Microsoft SQL Server will reject the data.

The following error will display in the Notifications tab in Stitch:

JSON table encountered too many errors, giving up. Rows: 1; errors: 1. JSON parsing error in row starting at position 0: . Nested arrays not allowed.

If possible, remove the offending record from the source.

A VARCHAR column is replicated to Microsoft SQL Server.

Microsoft SQL Server will store all VARCHAR data as NVARCHAR(450).

VARCHAR data is loaded that exceeds the current maximum size for the column.

Microsoft SQL Server will store all VARCHAR data as NVARCHAR(MAX).

A column containing date data with timezone info is replicated to Microsoft SQL Server.

Microsoft SQL Server will store the value as DATETIMEOFFSET(3).

A column contains timestamp data that is outside Microsoft SQL Server’s supported range.

Microsoft SQL Server will reject the records that fall outside the supported range.

The following error will display in the Notifications tab in Stitch:

timestamp out of range for Microsoft SQL Server on [TIMESTAMP]

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

To resolve the error, offending values in the source must be changed to be within Microsoft SQL Server’s timestamp range.

Use the _sdc_rejected table to identify the root of the issue.

A column contains integer data.

Integer values will be loaded to Microsoft SQL Server as the data type INT.

A column contains integer data that is outside Microsoft SQL Server’s supported range.

Microsoft SQL Server will reject the records that fall outside the supported range.

The following error will display in the Notifications tab in Stitch:

integer out of range for Microsoft SQL Server on [INTEGER]

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

To resolve the error, offending values in the source must be changed to be within Microsoft SQL Server’s limit for integers.

Use the _sdc_rejected table to identify the root of the issue.

A column contains decimal data.

Decimal values will be loaded to Microsoft SQL Server as the data type DECIMAL(38,6).

A column contains decimal data that is outside Microsoft SQL Server’s supported range.

Microsoft SQL Server will reject the records that fall outside the supported maximum range for the DECIMAL(38,6) data type.

The following error will display in the Notifications tab in Stitch:

Rejected records will be logged in the _sdc_rejected table of the integration's schema. Learn more.

To resolve the error, offending values in the source must be changed to be within Microsoft SQL Server’s limit for decimals.

Use the _sdc_rejected table to identify the root of the issue.

A new column is added in table already set to replicate.

If the column has at least one non-NULL value in the source, the column will be created and appended to the end of the table in Microsoft SQL Server.

Note: If the table using either Key- or Log-based Incremental Replication, backfilled values for the column will only be replicated if:

1. The records’ Replication Key values are greater than or equal to the last saved maximum Replication Key value for the table, or
2. The table is reset and a historical re-replication is queued.

A new column is added by you to a Stitch-generated table in Microsoft SQL Server.

Columns may be added to tables created by Stitch as long as they are nullable, meaning columns don’t have NOT NULL constraints.

A column is deleted at the source.

How a deleted column is reflected in Microsoft SQL Server depends on the Replication Method used by the table:

• Key-based Incremental: The column will remain in the destination, and default NULL values will be placed in it going forward.

• Log-based Incremental: Changes to a source table - including adding or removing columns, changing data types, etc. - require manual intervention before replication can continue. Refer to the Log-based Incremental Replication documentation for more info.

• Full Table: The column will remain in the destination, and default NULL values will be placed in it going forward.

You remove a column from a Stitch-replicated table in your destination.

The result of deleting a column from a Stitch-generated table depends on the type of column being removed:

• Primary Key columns: Changing a table’s Primary Key(s) is not permitted in Microsoft SQL Server. If Primary Key columns are changed, Stitch will stop processing data for the table.

• General columns: If new data is detected for the removed column, Stitch will re-create it in Microsoft SQL Server. This refers to all columns that are not prepended by _sdc or suffixed by a data type. For example: customer_zip, but not customer_zip__st.

  Note: An integration must support selecting columns AND you must deselect the column in Stitch for the column removal to be permanent.

• _sdc columns: Removing a Stitch replication column will prevent Stitch from loading replicated data into Microsoft SQL Server.

• Columns with data type suffixes: Removing a column created as result of accommodating multiple data types will prevent Stitch from loading replicated data into the table. This applies to columns with names such as: customer_zip__st, customer_zip__int, etc.

Indices are applied to Stitch-generated columns in the destination.

Stitch will respect the index application.

You switch to a different destination of the same type.

This means the destination type is still Microsoft SQL Server, Stitch may just be connected a different database in Microsoft SQL Server.

• For tables using Key-based or Log-based Incremental Replication, replication will continue using the Replication’s Key last saved maximum value. To re-replicate historical data, resetting Replication Keys is required.
• For tables using Full Table Replication, the table will be fully replicated into the new destination during the next successful job.
• For webhook integrations, some data loss may be possible due to the continuous, real-time nature of webhooks. Historical data must either be backfilled or re-played.