Everything in today’s digital world can be accessed and controlled online. This process generates a large amount of data, making it challenging to undertake real-time analysis, get insights, spot fraud, and abnormalities, warn users, and carry out other tasks.

Taboola is the most advanced participant in one of the most trusted but incredibly resilient categories in online advertising due to its business model. Superior Data Analytics is made possible by the Cloud-based, fully managed Snowflake data warehouse solution. AWS, Azure, and GCP are used by Snowflake to handle its cloud infrastructure and data. The data is subjected to SQL queries by Snowflake in order to convert and offer insights. You might need to transfer your Taboola Data into a Data Warehouse like Snowflake for further Analysis.

In this article, you will learn how to transfer data from Taboola to Snowflake using CSV files format and an automated method.

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Methods to Connect Taboola to Snowflake

Method 1: Connect Taboola to Snowflake using Hevo 

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The following steps can be implemented to connect Taboola to Snowflake using Hevo:

Step 1: Configure Taboola as your Source

Perform the following steps to configure Taboola as the Source in your Pipeline:

  • Step 1.1: Click PIPELINES in the Asset Palette.
  • Step 1.2: Click + CREATE in the Pipelines List View.
  • Step 1.3: In the Select Source Type page, select Taboola.
  • Step 1.4: In the Configure your Taboola Source page, specify the following:
Taboola to Snowflake: Configure Taboola Source
  1. Pipeline Name: A unique name for the Pipeline, not exceeding 255 characters.
  2. Client ID: The Client ID of your Taboola advertiser account
  3. Client Secret: The Client Secret of your Taboola advertiser account. NOTE: The Client ID and Client Secret are shared by your Taboola Account Manager in the onboarding email communication. You can request these again from the Taboola team if required.
  4. Advertiser Accounts: This field is displayed once you enter the correct Client ID and Secret. Select the advertiser accounts whose data you want to ingest.
  5. Historical Sync Duration: The duration for which historical data must be synced to the Destination. Default value: 1 Year.
  • Step 1.5: Click TEST & CONTINUE.
  • Step 1.6: Proceed to configuring the data ingestion and setting up the Destination.

Step 2: Configure Snowflake as your Destination

To set up Snowflake as a destination in Hevo, follow these steps:

  • Step 2.1: In the Asset Palette, select DESTINATIONS.
  • Step 2.2: In the Destinations List View, click + CREATE.
  • Step 2.3: Select Snowflake from the Add Destination page.
  • Step 2.4: Set the following parameters on the Configure your Snowflake Destination page:
    • Destination Name: A unique name for your Destination.
    • Snowflake Account URL: This is the account URL that you retrieved.
    • Database User: The Hevo user that you created in the database. In the Snowflake database, this user has a non-administrative role.
    • Database Password: The password of the user.
    • Database Name: The name of the Destination database where data will be loaded.
    • Database Schema: The name of the Destination database schema. Default value: public.
    • Warehouse: SQL queries and DML operations are performed in the Snowflake warehouse associated with your database.
Taboola to Snowflake: Configure Snowflake Destination
  • Step 2.5: Click Test Connection to test connectivity with the Snowflake warehouse.
  • Step 2.6: Once the test is successful, click SAVE DESTINATION.
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Method 2: Connect Taboola to Snowflake Manually using JSON Files

You cannot directly export the data from Taboola to Snowflake. To export data from Taboola to Snowflake, first you will have to export data from Taboola as JSON files and then load the JSON files into Snowflake.

Step 1: Export Data from Taboola as JSON

The first step in exporting data from Taboola to Snowflake is exporting data from Taboola as JSON files.

Step A: Making API Calls for Exporting Data

Developers can access the servers of Taboola and extract data via the Backstage the API. By calling API, for instance, you may obtain campaign data.

GET /backstage/api/1.0/[account-id]/campaigns/[campaign-id]/items/.
Step B: Retrieving JSON Response

The Backstage API for Taboola gives a JSON Response that resembles this:

      "id": "1",
      "campaign_id": "124",
      "type": "ITEM",
      "url": "http://news.example.com/article.htm",
      "thumbnail_url": "http://cdn.example.com/image.jpg",
      "title": "Demo Article",
      "approval_state": "APPROVED",
      "is_active": true,
      "status": "RUNNING"

Now you have your JSON Data with you. You can create a JSON file. The first step in exporting data from Taboola to Snowflake is complete now.

Step 2: Load JSON Data into Snowflake 

The second step in exporting data from Taboola to Snowflake is importing JSON data into Snowflake. 

Step A: Create Table and Load JSON Data

Run a straightforward create statement. With this command, a single-column table with the column “v” is created.

create or replace table json_table (v variant);

Utilize Snowflake’s PARSE_JSON function and a straightforward INSERT statement to load a JSON file. For example: 

insert into json_table
      "fullName":"Robert Downey",
      "address": {
          "suite":"916 West Burbank Blvd"
      "movies": [
          {"name":"Iron Man","budget":"$150M","producer":"Avi Arad"},
          {"name":"Sherlock Holmes","budget":"$200M","producer":"Joel Silver"},
          {"name":"Dolittle","budget":"$175M","producer":"Joe Roth"}

You have a collection of intricately nested objects in this example. In a real-world setting, you’d use snowpipe or a copy command. For example: 

copy into json_table from '@demo_stage/path_to_file/file1.json;


copy into json_table from 's3://demo_bucket/file1.json;

At load time, Snowflake divides the JSON into sub-columns depending on the key-value pairs. For optimization, these keys are saved in the metadata as pointers. Based on the schema definition inherent in the JSON string, structural information is generated dynamically (Schema-on-Read).

Step B: Retrieving and Casting Data

Let’s retrieve the information from the “fullName” sub-column.

select v:fullName from json_table;
1 Row Produced
1“Robert Downey”

The JSON sub-columns are indicated by a colon where:

  • The name of the column in the json table table is v.
  • In the JSON schema, fullName = attribute.
  • To specify which attribute in column “v” you wish to choose, use the notation v:fullName.

In the following step, you will cast the double-quoted table that was returned in the previous step into a proper data type.

select v:fullName::string as full_name from json_table;
1 Row Produced
1Robert Downey

Just like in standard SQL, you inserted an alias with “as” and used :: to cast to a string data type. Now it’s possible to search JSON data without having to learn a new programming language.

    v:fullName::string as full_name,
    v:age::int as age,
    v:gender::string as gender
from json_table
1 Row Produced
1Robert Downey55Male

Voila! You were successful in loading the data from JSON to Snowflake using the different Snowflake command. You have successfully done Taboola to Snowflake data transfer.

Limitations of Connecting Taboola to Snowflake Manually

  • Data can only be transferred in one direction from Taboola to Snowflake. Two-way sync is necessary to keep both tools current.
  • The manual process takes time because the records need to be updated often. This is a waste of time and resources that could be used for more crucial company duties.
  • Some customers may find the amount of engineering bandwidth needed to maintain workflows across numerous platforms and update current data bothersome.
  • Data transfer does not allow for any transformation. Businesses that want to modify their data before transferring it from Taboola to Snowflake may find this to be a significant drawback.


In this article, you got a glimpse of how to connect Taboola to Snowflake after a brief introduction to the salient features, and use cases. The methods talked about in this article are using automated solutions such as Hevo and JSON files. The second process can be a bit difficult for beginners. Moreover, you will have to update the data each and every time it is updated and this is where Hevo saves the day!

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Hevo provides its users with a simpler platform for integrating data from 150+ sources for Analysis. It is a No-code Data Pipeline that can help you combine data from multiple sources like Taboola. You can use it to transfer data from multiple data sources into your Data Warehouses, Database, or a destination of your choice such as Snowflake. It provides you with a consistent and reliable solution to managing data in real-time, ensuring that you always have Analysis-ready data in your desired destination.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand. You can also have a look at the unbeatable pricing that will help you choose the right plan for your business needs.

Share your experience of learning about Taboola to Snowflake! Let us know in the comments section below!

Harsh Varshney
Research Analyst, Hevo Data

Harsh is a data enthusiast with over 2.5 years of experience in research analysis and software development. He is passionate about translating complex technical concepts into clear and engaging content. His expertise in data integration and infrastructure shines through his 100+ published articles, helping data practitioners solve challenges related to data engineering.

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