Twilio Data Integration with BigQuery

With Portable, integrate Twilio data with your BigQuery warehouse in minutes. Access your customer engagement platform data from BigQuery without having to manage cumbersome ETL scripts.

The Two Paths to Connect Twilio to Google BigQuery

There are two ways to sync data from Twilio into your data warehouse for analytics.

Method 1: Manually Developing a Custom Data Pipeline Yourself

Write code from scratch or use an open-source framework to build an integration between Twilio and BigQuery.

Method 2: Automating the ETL Process with a No-Code Solution

Leverage a pre-built connector from a cloud-hosted solution like Portable.

How to Create Value with Twilio Data

Teams connect Twilio to their data warehouse to build dashboards and generate value for their business. Let’s dig into the capabilities Twilio exposes via their API, outline insights you can build with the data, and summarize the most common analytics environments that teams are using to process their Twilio data.

Extract: What Data Can You Extract from the Twilio API?

Twilio is a customer engagement platform used for building unique, personalized experiences.

To help clients power downstream analytics, Twilio offers an application programming interface (API) for clients to extract data on business entities. Here are a few example entities you can extract from the API:

  • Accounts
  • Addresses
  • Applications
  • BulkExport
  • Usage Records

You can visit the Twilio API Documentation to explore the entire catalog of available API resources and the complete schema definition for each.

As you think about the data you will need for analytics, don’t forget that Portable offers no-code integrations to other similar applications.

Regardless of the SaaS solution you use, it’s important to find a customer engagement platform with robust data available for analytics.

Load: Which Destinations Are Best for Your Twilio ETL Pipeline?

To turn raw data from Twilio into dashboards, most companies centralize information into a data warehouse or data lake. For Portable clients, the most common ETL pipelines are:

  1. Twilio to Snowflake Integration
  2. Twilio to Google BigQuery Integration
  3. Twilio to Amazon Redshift Integration
  4. Twilio to PostgreSQL Integration
Common Data Warehouses
Common Data Warehouses

Once you have a destination to load the data, it’s common to combine Twilio data with information from other enterprise applications like Jira, Mailchimp, HubSpot, Zendesk, and Klaviyo.

From there, you can build cross-functional dashboards in a visualization tool like Power BI, Tableau, Looker, or Retool.

Develop: Which Dashboards Should You Build with Twilio Data?

Now that you have identified the data you want to extract, the next step is to plan out the dashboards you can build with the data.

As a process, you want to consume raw data, overlay SQL logic, and build a dashboard to either 1) increase revenue or 2) decrease costs.

Replicating Twilio data into your cloud data warehouse can unlock a wide array of opportunities to power analytics, automate workflows, and develop products. The use cases are endless.

Now that we have a clear sense of the insights we can create, let’s compare the process of developing a custom Twilio integration with the benefits of using a no-code ETL solution like Portable.

Method 1: Building a Custom Twilio ETL Pipeline

To build your own Twilio integration, there are three steps:

  1. Navigate the Twilio API documentation
  2. Make your first API request
  3. Turn an API request into a complete data pipeline

Let’s walk through the process in more detail.

How to Interpret Twilio’s API Documentation

When reading API documentation, there are a handful of key concepts to consider.


There are many common authentication mechanisms. OAuth 2.0 (Auth Code and Client Credentials), API Keys, JWT Tokens, Personal Access Tokens, Basic Authentication, etc. For Twilio, it’s important to identify the authentication mechanism and how best to incorporate the necessary credentials into your API requests.

Twilio supports HTTP Basic authentication. This allows you to protect the URLs on your web server so that only you and Twilio can access them. In order to authenticate with HTTP, you may provide a username and password with the following URL format:

https://username:[email protected]/2010-04-01/your_desired_path

For HTTP Basic authentication, you will use your Twilio account SID as your username and your auth token as your password:

curl -G

You can find both your account SID and auth token in the Twilio Console after signing up for a free Twilio trial account.

If you want to use API keys to authenticate instead of your Twilio account SID and auth token, then use the API key as your username and your API keys Secret as your password.


It’s important to identify the Twilio API endpoints you want to use for analytics. Most APIs offer a combination of GET, POST, PUT, and DELETE request methods; however, for analytics, GET requests are typically the most useful. At times, POST requests can be used to extract data as well.

For Twilio, the messages endpoint is a great place to get started.

Request Parameters

For each API endpoint you would like to use for analytics, you need to understand the method (GET, POST, PUT, or DELETE) and the URL, but there are other considerations to take into account as well. You should look out for pagination mechanics, query parameters, and parameters that are added to the request path.

Twilio’s Programmable Chat client SDKs use paging to improve performance when accessing potentially large collections of chat objects. Public Channels, User Channels, and the Members list for each channel are exposed through Paginators. In JavaScript, Messages are also paged using Paginators. When requesting an initial set of any of these entities, your provided callback mechanism will receive a result indicating the success or failure of the operation as well as a paginator to access the items.

While the signature of the individual methods will vary by SDK platform, each paginator has the following accessors:

  • A way to obtain the items.
  • A boolean property indicating if there are subsequent pages.
  • A method taking the same callback mechanism as the original call to request the next page.

Some API endpoints require unique identifiers from a previous API response to be included in the URL path. For instance, to retrieve an account resource, you need a sid that is returned from another endpoint.

How Do You Call the Twilio API? (Tutorial)

  1. Follow the instructions above to read the Twilio API documentation
  2. Identify and collect your credentials for authentication
  3. Pick the API resource you want to pull data from
  4. Configure the necessary parameters, method, and URL to make your first request (e.g. with curl or Postman)
  5. Add your credentials and make your first API call . Here is an example request using curl (without real credentials):

How Do You Maintain a Custom Twilio to BigQuery ETL Pipeline?

Making a call to the Twilio API is just the beginning of maintaining a complete custom ETL pipeline.

Here is a getting-started guide to building a production-grade pipeline for Twilio:

  • For each API endpoint, define schemas (which fields exist and the type for each)
  • Process the API response and parse the data (typically parsing JSON or XML)
  • Handle and replicate nested objects and custom fields
  • Identify which Twilio fields are primary keys and which keys are required vs. optional
  • Version control your changes in a git-based workflow (using GitHub, GitLab, etc.)
  • Handle code dependencies in your toolchain and the upgrades that come with each
  • Monitor the health of the upstream API, and —when things go wrong— troubleshoot via the status page, reach out to support, and open tickets
  • Handle error codes (HTTP error codes like 400s, 500s, etc.)
  • Manage and respect rate limits imposed by the server

We won’t go into detail on all of the items above, but rate limits are a great example of the complexity found in a production-grade data pipeline.

Learn more about Twilio rate limiting.

Twilio Rate Limiting
Twilio Rate Limiting

If you don’t respect rate limits, and if you can’t handle server responses (like 429 errors with a Retry-After header), your pipeline can break, and analytics can become out-of-date.

What Are the Drawbacks of Building the Twilio ETL Pipeline Yourself?

You can probably tell at this point that there is a lot of work that goes into building and maintaining an ETL pipeline from Twilio to your data warehouse.

If you want less development work, faster insights, and no ongoing responsibilities, you should consider a cloud-hosted ETL solution.

Let’s walk through the setup process for a no-code ETL solution and its benefits.

Method 2: Using a No-Code Twilio ETL Solution

No-code ETL solutions are simple. Vendors specialize in building and maintaining data pipelines on your behalf. Instead of starting from scratch for each integration. Companies like Portable create connector templates that can be leveraged by hundreds or thousands of clients.

Step-By-Step Tutorial for Configuring Your Twilio ETL Pipeline

Off-the-shelf ETL tools offer a no-code setup process. Here are the instructions to connect Twilio to your cloud data warehouse with Portable.

  1. Create an account (no credit card required)
  2. Add a source —search for and select Twilio
  3. Authenticate with Twilio using the instructions in the Portable console
  4. Select BigQuery and authenticate
  5. Set up a flow connecting Twilio to your analytics environment
  6. Run your flow to replicate data from Twilio to your warehouse
  7. Use the dropdown to set your data flow to run on a cadence

What Are the Benefits of Using Portable for Twilio ETL?

No-Code Simplicity

Start moving Twilio data in minutes. Save yourself the headaches of reading API documentation, writing code, and worrying about maintenance. Leave the hassle to us.

Easy to Understand Pricing

With predictable, fixed-cost pricing per data flow, you know exactly how much your Twilio integration will cost every month.

Fast Development Speeds

Access lightning-fast connector development. Portable can build new integrations on-demand in hours or days.

Hands-On Support

APIs change. Schemas evolve. Twilio will have maintenance issues and errors. With Portable, we will do everything in our power to make your life easier.

Unlimited Data Volumes

You can move as much data from Twilio to Google BigQuery as you want without worrying about usage credits or overages. Instead of analyzing your ETL costs, you should be analyzing your data.

Free to Get Started

Sign up and get started for free. You don’t need a credit card to manually trigger a data sync, so you can try all of our connectors before paying a dime.

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