Shopify Webhook to Snowflake Integration: 2 Easy Methods

on Shopify, Snowflake, Webhook • July 28th, 2022 • Write for Hevo

Shopify Webhook to Snowflake FI

E-commerce businesses, including online stores, are experiencing phenomenal growth, and an increasing number of people are switching their focus to e-commerce enterprises. Shopify is a type of e-commerce platform that allows users to quickly and easily set up their online stores.

Because of the exponential growth of data in the current environment, businesses worldwide are being forced to spend money on hardware resources to simply keep up with the massive amounts of data they have. Businesses are rapidly shifting their focus toward cloud-based data warehouses like Snowflake, which are more affordable but also secure and scalable.

Connecting Shopify Webhook to Snowflake helps in fetching data when any specific event occurs. In this article, you will learn about Shopify and Snowflake. You will read about the two methods to connect Shopify Webhook to Snowflake.

Table of Contents

What is Shopify?

Shopify Webhook to Snowflake: shopify logo
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The e-commerce platform known as Shopify makes it possible for users to construct an online store as well as retail point-of-sale systems in a matter of minutes. It is a market-leading online store builder that is used extensively by both novices and experienced users. This platform makes it easy for business owners to manage their operations by providing design templates, website hosting, marketing tools, and even a blog for their use. 

Shopify is a great option for first-time online business owners who want to get their feet wet by opening a modest-sized storefront before eventually transitioning to a personal website. Shopify’s user-friendly interface makes it possible for users to construct online stores without the need to write even a single line of code, which means that users do not require any prior experience or training to get started with building a Shopify site.

Key Features of Shopify 

  • Analytics and Reporting: Shopify gives users access to a plethora of marketing tools, including built-in tools for analytics and reporting, as well as marketing tools for email marketing.
  • Pre-built Themes: Shopify comes with hundreds of pre-built and ready-to-set up themes of all different categories, allowing users to set up an online store in just a few minutes. Shopify users also have the option to build their custom themes from scratch. Live Search and Drop-Down Menus are both included in the package.
  • App Integrations: Shopify allows its users to integrate their stores with a variety of third-party apps and services, which results in an improved user experience and increased accessibility.

What is Snowflake?

Shopify Webhook to Snowflake: snowflake logo
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Snowflake is a cloud data warehouse platform that is offered as a SaaS solution to users. It leverages the ANSI SQL protocol that allows it to handle structured and semi-structured data formats like JSON, XML, and Parquet. 

Snowflake employs shared disk architecture, which allows all compute nodes in the platform to access a common data repository for persisting data. Snowflake also executes queries utilizing MPP compute clusters, which use shared-nothing architecture to store a subset of the complete data set locally on each node in the cluster, which helps with performance control. In a shared-nothing configuration, each computational node has its private memory and storage or disk space.  

In Snowflake, virtual warehouses are formed by combining many computing clusters. To access the same storage layer, numerous virtual warehouses may be built without the requirement for multiple copies of the data in each warehouse. These virtual warehouses may be scaled up and down with little to no downtime or storage effect.

Key Features of Snowflake

  • Scalability: Snowflake’s multi-cluster architecture facilitates separate computing and storage resources. This design allows it to scale up and down following business needs. Users of Snowflake also have access to auto-scaling features, enabling Snowflake to start and terminate clusters automatically during resource-intensive processes.
  • Better Analytics: By switching from nightly batch loads to real-time data streams, Snowflake helps optimize your analytics workflow. Providing safe, concurrent, and controlled access to your data warehouse throughout your organization may improve the quality of your analytics. This enables companies to effectively use resources to maximize income while lowering expenses and reducing human labor.
  • Cloning: Another key aspect of the Snowflake cloud data warehouse is cloning. The zero-copy functionality in Snowflake allows you to quickly clone any database or table without having to produce a new copy. It does it by keeping track of clone changes in its metadata store while still referring to the same data files in the backend. Zero-copy cloning has the benefit of allowing you to create several independent clones of the same data without incurring additional costs. 

Why Connect Shopify Webhook to Snowflake?

The process of connecting Shopify Webhook to Snowflake offers a number of advantages. You have the option of selecting the data that should be replicated, and this applies to each destination where you would like your Shopify data to be replicated to.

You have the option of getting the raw data, or you can explore all of the nested API objects in separate tables. You have the ability to add any dbt transformation model you want and even sequence them in the order that best suits your needs in Shopify Webhook to Snowflake Integration. As a result, the data can be obtained in Snowflake in the precise format that you require.

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If yours is anything like the 1000+ data-driven companies that use Hevo, more than 70% of the business apps you use are SaaS applications Integrating the data from these sources in a timely way is crucial to fuel analytics and the decisions that are taken from it. But given how fast API endpoints etc can change, creating and managing these pipelines can be a soul-sucking exercise.

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Methods to Connect Shopify Webhook to Snowflake

There are two methods to connect Shopify Webhook to Snowflake:

Method 1: Connect Shopify Webhook to Snowflake using Hevo

Shopify Webhook to Snowflake: hevo logo
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Hevo provides Snowflake as a Destination for loading/transferring data from any Source system, which also includes Shopify Webhook. You can refer to Hevo’s documentation for Permissions, User Authentication, and Prerequisites for Snowflake as a destination here

Configure Shopify Webhook 

Configure Shopify Webhook as a Source in your pipeline for Shopify Webhook to Snowflake Integration:

  • Step 1: From the list of sources provided, select Shopify as the source.
  • Step 2: Enter the Pipeline name and click Continue.
  • Step 3: In this step, you will be given the option to select the destination (If already created). You can either choose an existing destination or create a new one by clicking on the ‘Create New Destination’ button to connect Shopify Webhook to Snowflake.
  • Step 4: On the final settings page, you will be given the option to select ‘Auto-Mapping’ and JSON parsing strategy. 
  • Step 5: Click Continue to integrate Shopify Webhook to Snowflake. You should be seeing a webhook URL generated on the screen.
  • Step 6: Copy the generated webhook URL and add it to your Shopify account to connect Shopify Webhook to Snowflake.

Configure Snowflake as a Destination

To set up Snowflake as a destination in Hevo for Shopify Webhook to Snowflake Integration, follow these steps:

  • Step 1: In the Asset Palette, select DESTINATIONS.
  • Step 2: In the Destinations List View, click + CREATE.
  • Step 3: Select Snowflake from the Add Destination page.
  • Step 4: Set the following parameters on the Configure your Snowflake Destination page to integrate Shopify Webhook to Snowflake:
Shopify Webhook to Snowflake: configure snowflake
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  • Destination Name: Give your destination a unique name.
  • Database Cluster Identifier: The IP address or DNS of the Snowflake host is used as the database cluster identifier.
  • Database Port: The port on which your Snowflake server listens for connections is the database port. 5439 is the default value.
  • Database User: In the Snowflake database, a user with a non-administrative position.
  • Database Password: The user’s password.
  • Database Name: The name of the destination database into which the data will be loaded.
  • Database Schema: The Destination database schema’s name. The default setting is public.
  • Step 5: To test connectivity of Shopify Webhook to Snowflake Integration, click Test Connection.
  • Step 6: When the test is complete, select SAVE DESTINATION.

Deliver Smarter, Faster Insights with your Unified Data

Using manual scripts and custom code to move data into the warehouse is cumbersome. Changing API endpoints and limits, ad-hoc data preparation, and inconsistent schema makes maintaining such a system a nightmare. Hevo’s reliable no-code data pipeline platform enables you to set up zero-maintenance data pipelines that just work.

  • Wide Range of Connectors: Instantly connect and read data from 150+ sources including SaaS apps and databases, and precisely control pipeline schedules down to the minute.
  • In-built Transformations: Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
  • Near Real-Time Replication: Get access to near real-time replication for all database sources with log-based replication. For SaaS applications, near real-time replication is subject to API limits.   
  • Auto-Schema Management: Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps the source schema with the destination warehouse so that you don’t face the pain of schema errors.
  • Transparent Pricing: Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow.
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Method 2: Manually Connect Shopify Webhook to Snowflake 

If you want to manually code the scripts necessary to set up the connection from Shopify Webhook to Snowflake, you can use this method. Full disclosure, if you want to spend time building and managing pipelines, you should choose this method. Choose a solution that does the heavy lifting for you instead if you want to save time for other, more important tasks. This will allow you to save time in Shopify Webhook to Snowflake Integration.

For the Shopify Webhook to Snowflake Integration, you need to first connect Shopify Webhook to Redshift and then connect Redshift to Snowflake.

Connect Shopify Webhook to Redshift

The first step in Shopify Webhook to Snowflake Integration is to connect Shopify Webhook to Redshift. There are only six easy steps required to do this:

  • Step 1: After logging into your Shopify account for the first time, you will need to initiate the creation of a Shopify Webhook. In this section, you will be prompted to select the events for which you wish to send data when that particular event occurs. After you have decided on the data format, URL, and webhook API version, you are ready to proceed to the next step in the process.
  • Step 2: The next step is to retrieve the AWS Redshift Cluster Public Key as well as the Cluster Node IP Addresses.
  • Step 3: Establishing a safe SSL connection between the remote host and the Amazon Redshift cluster can be done with the help of the Amazon Redshift Cluster Public Key.
  • Step 4: Creating a manifest file on your local machine is the next step in the process, which you can read more about here. The manifest file will have entries for the SSH host endpoints and the commands that need to be executed on the machine before the data can be sent to Amazon Redshift.
  • Step 5: The manifest file can then be uploaded to an Amazon S3 Bucket, and read permissions can be granted to all of the users who have access to the bucket.
  • Step 6: In conclusion, to load data into Amazon Redshift, you can connect to your local machine by using the COPY command and then load the data into Redshift which was extracted from Shopify Webhook.

You can click here to access a comprehensive guide that will walk you through the steps that were just mentioned.

Connect Redshift to Snowflake

The only method available for migrating data from Amazon Redshift to Snowflake is the migration-only approach, which involves cloning schemas and tables within Redshift. You can run both outdated and up-to-date procedures with this. You will be able to gain the necessary confidence through the use of this side-by-side approach while you are in the transformation phase itself. 

For this method, the schemas and tables that were developed in Redshift must be cloned while avoiding significant alterations to the data structure. The secret to successfully migrating large, complicated systems that are rife with dependencies is to confine one’s attention solely on the migration process, without making any changes to the structure. This method also enables you to easily compare the data stored on the old system and the new system while simultaneously operating both of them in parallel. This gives you the confidence to make the switch when the time comes.

In a nutshell, the migration-only approach is useful for simultaneously comparing data from the legacy system and the new one, bringing about gradual improvements in operational efficiency and maturity.

Limitations of Manually Connecting Shopify Webhook to Snowflake

Since the manual method of Shopify Webhook to Snowflake Integration involves transferring data from Redshift to Snowflake, a number of difficulties arise:

  • Amazon Redshift and Snowflake both use different variants of SQL syntax, which may cause some users to experience confusion. Even though some people favor Snowflake’s “correct syntax,” Redshift’s approach to SQL’s syntax is more lenient than Snowflake’s when it comes to deleting tables, so the DML changes were widely visible. For instance, Redshift can work with delete_name even when the “from” keyword is absent.
  • The Snowflake Information Schema uses only capital letters, which may come to be interpreted as a nuance. In addition, while you are using the UPPER function with the SELECT query, you might run into schema problems. Snowflake will return the following error message if the Information Schema is not selective enough: “Information schema query returned too much data.”
  • Because the default account time zone setting for Snowflake is America/Los Angeles, the clock time for the database is set to Pacific Standard Time (PST). Many times, teams will become stuck because of the different time zones, which has the potential to become a significant barrier on your journey to migrate data. You can get around this difficulty by adjusting the time zone settings to suit your requirements.
  • The problem is with the date, yes. You will discover that Redshift was significantly more lenient when it came to storing future dates in a timestamp column during the migration, simply because Snowflake does not accept them. In addition, you will see an error message that does not provide sufficient detail. The team from Instamart solved the problem by using the NULL IF operator in the copy command.

Conclusion

To conclude, you have learned two methods to connect Shopify Webhook to Snowflake. In the first method, you created a Hevo pipeline that automatically migrates data from Shopify Webhook to Snowflake. The second method is manually connecting the two through Amazon Redshift.

In this article, you learned two methods to perform Shopify Webhook to Snowflake Connection and the key features of both respectively. 

However, as a Developer, extracting complex data from a diverse set of data sources like Databases, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to your Database can seem to be quite challenging. If you are from non-technical background or are new in the game of data warehouse and analytics, Hevo can help!

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