Are you already tracking event data with Segment and wish to consolidate that data into a data warehouse like Snowflake? In this post we compare two front-line approaches for moving data from Segment to Snowflake:  the first approach involves using Segment itself to push event data to Snowflake while the second approach uses Hevo to significantly multiply flexibility and ease of use while migrating your event data to Snowflake.

This blog will talk about both the approaches to move data from Segment to Snowflake. You can weigh the pros and cons of both approaches and decide on the one that suits you best. 

Understanding Segment

Segment to Snowflake: Segment
Image Source: Google

Segment allows you to integrate event data from your various web and mobile applications into a single platform and provides multiple destinations for the captured data. Data tracked with Segment is primarily user/customer activity, marketing, and analytics data across a company’s apps and platforms.

Understanding the Key Features of Segment

Some key features of Segment are as follows:

  1. Single View for Customer: Segment unifies your customer’s data from all platforms.
  2. Usage of a Single API: You can use a single API to collect the analytics data across any platform.
  3. Protect Data Integrity: With its tracking schema and proper enforcement of protocols, you can prevent any data quality issue.
  4. Personalized Interactions: Segment builds audience to power personalized experience.

Understanding Snowflake

Segment to Snowflake: Snowflake
Image Source: Google

Snowflake is a Cloud Data Warehouse built on a multi-cluster, micro-partitioning architecture that features a cost-efficient software-as-a-service operating model that is attractive to businesses of all sizes. Snowflake has been gaining recently in popularity and is now used widely across multiple markets and industry verticals. You can read more about Snowflake here.

Understanding the Key Features of Snowflake

Some key features of Snowflake are listed below:

  1. Unique Architecture: Snowflake has a hybrid architecture of shared-disk database architecture and shared-nothing database architecture. It provides faster and better performance to Snowflake.
  2. Support Semi-structured Data: Snowflake supports semi-structured data such as JSON, Avro, ORC, XML, etc. A special column type – VARIANT can be used for sem-structured data.
  3. Secured Data Sharing: Snowflake supports secured account-to-account data-sharing through tables, secure UDFs, and secure views.
  4. Virtual Compute Warehouse: Snowflake supports a virtual warehouse for your queries. Each virtual data warehouse is your MPP compute cluster composed of various compute nodes.
Segment to Snowflake: 2 Approaches to Move Data

Method 1: Building Custom Code to Load Data from Segment to Snowflake

Set up a native integration to move data from within Segment

Method 2: Using Hevo’s No-code Data Pipeline to Move Data Segment to Snowflake

Hevo Data can help you export data from Segment to Snowflake in real-time free of cost, without having to write a single line of code. With the help of Hevo’s pre-built integrations with 100+ data sources (including 30+ free sources such as Segment), you can set up the whole data pipeline without any technical intervention and load data to Snowflake or a destination of your choice with ease.


Methods to Move Event Data from Segment to Snowflake

Method 1: Migrating Event Data from Segment to Snowflake

For the purpose of this blog, let us take a use case where we are tracking website signup events with Segment, and we want to set up a connection to migrate that event data from Segment to Snowflake.

We already have our web asset setup in Segment and our Snowflake destination is ready so we will now explore the steps for migrating the event data from our web asset from Segment to Snowflake:

Segment to Snowflake: Select Snowflake
Image Source: Google
  1. Click on Destinations in the side navbar, then select Warehouses from the top navbar. 
  2. You will then be presented with a list of data warehouses to choose from. Select Snowflake. 
  3. Following that, you will need to fill the form shown below with your Snowflake account settings. 
  4. After filling in your credentials, click Connect to test and establish the connection to your Snowflake data warehouse.
  5. Finally, click on Connections on the left navbar to view your new connection and toggle the enable widget if necessary to start syncing data between Segment and Snowflake. 

Testing the Event Data Migration 

After waiting for a short while, you should start seeing your data in Snowflake. Follow these steps to verify:

  1. In Snowflake, click on the Worksheets icon in the main horizontal navbar.
  2. Click the ‘+’ tab to open a new worksheet
  3. Run a SELECT query in the worksheet using the format below to see your data:
  1. The screenshot below applies a similar query to show the synced data
Querying Data in Snowflake
Image Source: Google

Note: as mentioned earlier, the Segment will create a schema for you during the migration. In the screenshot, it is SCOLA_SIGNUP based on my Segment settings for this project. Yours will reflect your own project settings. The data will then be stored in the PAGES table under the Segment-created schema.

Segment to Snowflake: Limitations of Migrating Data Directly

Although Segment is quite robust in terms of the different event sources supported and the many tools you can leverage to get insights from your event data, it is rather limited for event data migration to a data warehouse in the following ways:

  1. Cannot Load Historical Data: If you are at a stage where you are trying to move data from Segment to Snowflake, then surely you have loads of historical events data that is stored in a different system (eg. a database). Segment, however, can only migrate “live” event data from your applications directly. In cases like this, you will need to figure out an alternative way to move historical data to Snowflake. 
  2. Cannot Load Data in Real-time: If you are on Segment’s free/team plan, then you would not be able to sync data to Snowflake in real-time. The free plan allows you to load data once every day and the team plan allows you to load data twice. If your team relies on the real-time availability of this data, then the native integration approach will not work for you.
  3. No Support for Data Transformations: Although Segment provides you some basic filtering, often data transformation use cases span much beyond that. For example: in case you want to convert time zones into a single format, or if you need to standardize currency values, etc. you will need to opt for a separate infrastructure that can cater to this. This imposes a significant performance cost depending on the size of data migrated, as well as creating additional dependencies in production.

Method 2: Segment to Snowflake Using Hevo Data

Using Hevo
Image Source

Hevo Data is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. It supports 100+ data sources (including 30+ free data sources) and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using various BI tools such as Power BI, Tableau, etc. 

Hevo focuses on two simple steps to move your data from Segment to Snowflake:

  • Configure Source: Connect Hevo Data with Segment by setting up a webhook.
Configuring Webhook to connect to Segment
Image Source: Self

Integrate Data: Complete Segment to Snowflake migration by providing your destination name, account name, region of your account, database username and password, database and schema name, and the Data Warehouse name.

Image Source: Self

Check Out What Makes Hevo Amazing:

  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
  • Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  • Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
  • Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
  • Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.


In this blog, you have learned how to connect the Segment to Snowflake manually. You also came across the various limitations of connecting Segment to Snowflake manually. So, if you are looking for a fully automated data pipeline, then try Hevo.

Hevo Data, a No-code Data Pipeline provides you with a consistent and reliable solution to manage data transfer between a variety of sources and a wide variety of Desired Destinations with a few clicks.

Visit our Website to Explore Hevo

Hevo Data with its strong integration with 100+ sources (including 30+ free sources such as Segment) allows you to not only export data from your desired data sources & load it to the destination of your choice such as Snowflake, but also transform & enrich your data to make it analysis-ready so that you can focus on your key business needs and perform insightful analysis using BI tools. 

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Share your experience of moving data from Segment to Snowflake in the comments section below!

Freelance Technical Content Writer, Hevo Data

Monty is passionate about solving the intricacies of data integration and analysis to data teams by offering informative content to help data teams in understanding these complex subjects.

No-code Data Pipeline For Snowflake