Resources for learning about how Stitch loads and organizes data into your destination.


Data Loading by Destination

Every destination handles data differently. Learn about what your destination supports, what it doesn’t, and how Stitch will load your data as a result.

Microsoft Azure SQL Data Warehouse Data Loading Behavior

Learn how Stitch will load data from your integrations and handle various scenarios into a Microsoft Azure destination.


Additional Resources

These resources contain additional detail that builds upon the info covered in each destination’s data loading guide. Learn more about how Stitch structures the schemas it creates for integrations, how structural changes are handled, how to resolve record rejections, and more.

Amazon Redshift Data Loading Reference

Learn how Stitch will load data from your integrations into Stitch’s Amazon Redshift destination.

Panoply Data Loading Reference

Learn how Stitch will load data from your integrations into Stitch’s Panoply destination.

Google BigQuery Loading Reference

Google BigQuery (v1) Data Loading Reference

Learn how Stitch will load data from your integrations into version 2 of Stitch’s Google BigQuery destination.

Google BigQuery (v2) Data Loading Reference

Learn how Stitch will load data from your integrations into version 2 of Stitch’s Google BigQuery destination.

Destination Data Loading Reference Guides

Every destination handles data differently. Learn about what your destination supports, what it doesn’t, and how Stitch will load your data as a result.

PostgreSQL Data Loading Reference

Learn how Stitch will load data from your integrations into Stitch’s PostgreSQL destination.

Snowflake Data Loading Reference

Learn how Stitch will load data from your integrations into Stitch’s Snowflake destination.

Understanding Integration Schema Structures in Your Destination

Learn how Stitch organizes the data replicated from your sources in your data warehouse.

Table Structural Changes

From time to time, Stitch will encounter data that can’t be loaded losslessly into the destination table in your destination. When this happens, Stitch may have to alter the structure of the table in order to successfully load the data.

Nested JSON Data Structures & Row Count Impact

MongoDB and many SaaS integrations use nested structures, which means each attribute (or column) in a table could have its own set of attributes. Depending on the type of destination you’re using, Stitch may deconstruct these nested structures into separate tables.

Querying Append-Only Tables

In this article, we’ll cover how append-only replication works and how to account for it in your queries.

Identifying & Resolving Rejected Record Issues

From time to time, Stitch may run into problems when attempting to load data into your destination. When data is deemed incompatible by the destination, the record will be rejected and Stitch will log it in a rejected records log.

Stitch and Destination Reserved Keywords

A reference of Stitch and destination-reserved keywords.

System tables and columns

When data is loaded into your destination, Stitch will create some additional columns and tables. Learn about these system columns and tables and how Stitch uses them.

Primary Key System Table (_sdc_primary_keys)

Some of Stitch’s destinations don’t have native support for Primary Keys. To ensure data can be de-duped during loading, Stitch will create a Primary Keys table for each integration schema.

Data Typing in Stitch

Google BigQuery and Storing Nested Data Structures

Understand how Stitch loads nested data structures in version 2 of the Google BigQuery destination.

Understanding Loading Behavior

Learn about the methods Stitch uses to load data into your destination and what the impact will be on your destination tables.