Customer demand is in a constant state of fluctuation. Companies must keep pace or risk losing their position in a crowded market. Digital transformation is the driver to helping companies remain agile to meet their customers’ needs. The Snowflake data warehouse provides massive storage capabilities to facilitate combining figures from disparate systems. These figures help inform decision-making and provide valuable insight into driving business strategies. In this overview, we’ll discuss the purpose of this popular API and walk you through how to generate a Snowflake API integration from

Table of Contents

  1. What Functions Are Available When You Generate a Snowflake API Integration?
  2. Generate a Snowflake API Integration to Drive the ETL Workflow
  3. Items Required to Generate a Snowflake API Integration
  4. Steps to Generate a Snowflake API Integration from
  5. How Can Help

What Functions Are Available When You Generate a Snowflake API Integration?

The Snowflake API provides functions to perform operations on database objects. It also provides the functions required to extend the platform.  

Accessing Information

Companies find Snowflake easy to use because it supports many of the standard functions defined in SQL. A few of these functions include:




Extending Snowflake

User-Defined Function (UDF) - A UDF enables the ability to perform functions not available via the system-defined functions.

Snowpark - The Snowpark API is a library for building applications to interact directly with the warehouse without having to move the information to storage

External Functions - An external function is a UDF that allows the platform to access external API services. The benefit is that it simplifies the pipeline by eliminating the coding required to keep the information from external systems up to date. 

Stored Procedures - With stored procedures, companies can combine SQL with JavaScript to implement programming constructs such as branching and looping. 

With advanced features of’s Snowflake integration, you can access the information in the platform using these functions and an entire catalog of additional functions.

Generate a Snowflake API Integration to Drive the ETL Workflow

The platform offers more than mere storage. The platform supports the Extract, Transform and Load (process) used for implementing continuous data pipelines.  


Snowpipe is integrated into the platform to support continuous ingestion. Snowpipe loads information directly from files in the staging storage space. These loads take place minutes after the information is staged.

Kafka Connector

The platform supports reading information from Apache Kafka topics. This connector allows the streaming of data asynchronously. The application publishes the information to the topic, and the Kafka connector from the warehouse reads the messages directly from Kafka.

Change Data Capture

The Change Data Capture (CDC) function records the changes that occur to any table within the warehouse. This includes updates, inserts and other data manipulation (DML) changes.

Recurring Tasks

A recurring task is a SQL statement that can be scheduled to run on a recurring schedule. Statements can be chained together to create more complex processing. 

Items Required to Generate a Snowflake API Integration

The API is the intermediary that makes integrations possible. As a cloud-based data warehouse, it can store both structured and semi-structured information from a variety of sources. Connecting to the warehouse requires one of the following items:

  • Driver
  • Connecter
  • Client API (SQL)

The platform supports developing applications using any of the below languages:

  • Go Language
  • Java
  • .NET
  • Node.js
  • C Language
  • PHP
  • Python provides a connector to integrate information from Snowflake. There is no coding required to build data pipelines in

Steps to Generate a Snowflake API Integration from provides a pre-built integration through what is known as a Snowflake Destination component. Implementing this connector requires the following steps:

1 - Create a Connection

A connection contains the properties needed to interact with the warehouse:

2 - Set Destination Properties

Destination Properties define the resources the connection requires. Properties needed at this step are the Target Schema and Target table. If either of these resources does not exist, the platform automatically creates them.

3 - Set the Operation Type

The operation type specifies the behavior required for the connection. The operations supported are:

Append - Data is appended to the target table

Overwrite (Truncate and Insert) - Information is truncated in the target table before inserting new information.

Merge (Insert and Delete) - Incoming information is compared to the target information. Anything that exists in both data sets is deleted before inserting new information. 

Merge (Update and Insert) - New information is merged by updating information in the target table and inserting new information into the table.

4 - Set Pre and Post SQL Actions

This property defines SQL actions that need to be executed before or after inserting the information. If the merge operation is selected, the Pre-action SQL code is executed before the staging table is created. The Post SQL action executes after merging the staging and target tables.

5 - Perform Schema Mapping

Schema mapping is the process of mapping the input field to the target table’s columns. 

Developing APIs can be a complex, time-consuming, and expensive process. It can also expose your organization to a number of risks including consistency, quality, and developer resourcing. DreamFactory is a REST API generation platform for a range of databases and other data sources. It gives you the ability to generate secure and fully documented APIs in a matter of minutes. Ready to get started?  Sign up for a 14-day free trial and start creating your APIs today.

How Can Help Integrate Snowflake streamlines the entire ETL process for integration teams. Even if they lack data engineering experience, they can create a pipeline up and running in a manner of minutes. This no-code/low-code tool extracts information from any source and loads it into the warehouse. Now you can use this merged information to provide real-time insights about key performance indicators. Best of all, there’s no complicated code. is your all-in-one data management solution for building pipelines. Now’s the time to consolidate your data into a Snowflake data warehouse to get the most value from your company’s data assets. Learn how connects with Snowflake with a seven-day demo.