Taboola to BigQuery

This page provides you with instructions on how to extract data from Taboola and load it into Google BigQuery. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

About Taboola

Taboola calls itself a “discovery platform” or a “reverse search engine.” It delivers personalized content recommendations to more than a billion users who visit many of the web’s most popular websites every month. You’ve probably seen them yourself – a block of images and headlines labeled “Sponsored Links by Taboola.” The links are designed to increase user engagement with the sites on which they appear.

What is Google BigQuery?

Google BigQuery is a data warehouse that delivers super-fast results from SQL queries, which it accomplishes using a powerful engine dubbed Dremel. With BigQuery, there's no spinning up (and down) clusters of machines as you work with your data. With all of that said, it's clear why some claim that BigQuery prioritizes querying over administration. It's super fast, and that's the reason why most folks use it.

Getting data out of Taboola

Developers can pull data out of Taboola’s servers using its Backstage API to create JSON output. For instance, you can fetch a JSON formatted list of information about a campaign with an HTTP GET request:

GET /backstage/api/1.0/[account-id]/campaigns/[campaign-id]/items/
Host: https://backstage.taboola.com
Authorization: Bearer [access-token]

The response might look like this:

{
  "results":[
      {
      "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"
    }
    ]
  }

Loading data into Google BigQuery

Google Cloud Platform offers a helpful guide for loading data into BigQuery. You can use the bq command-line tool to upload the files to your awaiting datasets, adding the correct schema and data type information along the way. The bq load command is your friend here. You can find the syntax in the bq command-line tool quickstart guide. Iterate through this process as many times as it takes to load all of your tables into BigQuery.

Other data warehouse options

BigQuery is really great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Postgres or Redshift, which are two RDBMSes that use similar SQL syntax. If you're interested in seeing the relevant steps for loading this data into Postgres or Redshift, check out To Redshift and To Postgres.

Easier and faster alternatives

If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.

Thankfully, products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Taboola data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your Google BigQuery data warehouse.