PortablePortable Logo

Does RudderStack Connect to BigQuery?

Does RudderStack Connect to BigQuery? Find The Best BigQuery ETL Solution!

BigQuery is one of the premier data warehouses on the market, and RudderStack is a notable ETL tool to evaluate. Let's evaluate your options for BigQuery ETL and the capabilities of RudderStack specifically.

Need a BigQuery ETL Solution Today?

If you want to start moving data from 300+ business applications into BigQuery with no code, you can use Portable for free.

It takes only a few minutes to start syncing data to BigQuery with Portable.

  1. Create your Portable account
  2. Choose one of the 300+ data sources we support (or request a new source)
  3. Input your credentials using the instructions in the Portable application
  4. Create a BigQuery environment and authenticate with your credentials
  5. Connect your data source to BigQuery by creating a data flow
  6. Sync data to BigQuery to try things out
  7. Run your data flow on a cadence (daily, hourly, etc.)

Why do Companies Evaluate RudderStack for BigQuery ETL?

RudderStack was founded in , a customer data platform for real-time data pipelines. RudderStack is a CDP built for developers. The solution is purpose-built for collecting customer data from websites and mobile apps and syncing the data into a downstream application or data warehouse. In addition to data collection, the platform is capable of both ETL and Reverse ETL for customer data.

When data teams evaluate SaaS ETL / ELT solutions, it is common for RudderStack to be on the list. As teams build out their Modern Data Stack, it's common to first pick a solution like BigQuery for data warehousing, and then to evaluate the best ETL solutions.

Let's walk through the pros and cons of using RudderStack for BigQuery ETL.

The Pros And Cons of RudderStack for BigQuery ETL?

When evaluating ETL tools for BigQuery, the goal is to automate the process of extracting data from APIs, databases, or files, and the data pipeline that loads the data into BigQuery.

Before the advent of cloud-hosted ETL / ELT solutions like Portable and RudderStack, it was common for data engineers to write Python code, deploy infrastructure, use an open source framework, or pay consultants to manage these data pipelines.

With no-code solutions, this process is now much simpler. Let's take a look at RudderStack's capabilities.

What functionality is included with RudderStack?

  1. Easy deployment of data collection from your website or mobile application
  2. ETL from common customer data applications (HubSpot, Salesforce, etc.) into your data warehouse
  3. Compatibility with Segment for simple migration
  4. 200+ Destinations

Whether you're on AWS, Microsoft Azure, or Google Cloud Platform. Using a no-code solution can make the data syncing process extremely simple.

It's common for companies to use RudderStack connectors for the largest data sources and to use Portable for hard-to-find systems.

What functionality is included with Portable?

  1. 300+ data source connectors
  2. Support for the major data warehouses as destinations
  3. Unlimited data volumes
  4. Free development of new data sources
  5. Email and Slack notifications
  6. Hands-on support and maintenance

Now, let's take a look at the process of replicating data with RudderStack.

Extracting Data with RudderStack

RudderStack specializes in data integration. Extracting data from disparate data sources and then loading into destinations like BigQuery.

Can RudderStack Load Data to BigQuery?

RudderStack supports a number of destinations - Here are some of the destinations that RudderStack supports:

At Portable, we support BigQuery, and we support the most common data warehouses.

  • Snowflake
  • BigQuery
  • Redshift
  • PostgreSQL
  • MySQL

Now let's dig into the types of data sources that you will be able to connect to your data warehouse.

Which Data Sources Does RudderStack Support?

When you evaluate ETL tools, there are two main considerations when it comes to connectors. The prebuilt connectors that are already supported, and custom connector development.

RudderStack Prebuilt Connectors

RudderStack offers strong SDK capabilities that make it easy to collect data from websites and mobile apps.

In addition to data collection, Rudderstack supports 50+ customer data applications (common platforms like Mailchimp, Customer.io, etc.) out-of-the-box.

Portable Prebuilt Connectors

Portable provides access to 300+ data sources out-of-the-box. With a catalog larger than most other ETL tools, it's easy to connect the sources you need to your analytics environment of choice.

Uniquely, Portable focuses on long-tail business applications. This means that the connectors in Portable's catalog are hard-to-find and are great for augmenting your primary ELT vendor for the no-code connectors you need as your responsibilities expand.

RudderStack to BigQuery Pricing?

So, how much will it cost to connect your data sources to BigQuery? First, let's walk through RudderStack's pricing model.

RudderStack charges primarily on events per month.

  1. Free plan - Includes up to one million events per month (data can be collected via SDKs and synced to data warehouses)
  2. Starter plan - Starts at $500 per month and includes additional event volumes, near real-time data, support and SLAs
  3. Growth plan - Includes profiles, reverse ETL, ETL pipelines, and dedicated support
  4. Enterprise plan - Includes premium support, HIPAA, and SSO

If you need long-tail integrations that aren't supported by RudderStack, you should give Portable a try.

Portable's pricing model is focused on simplicity. It's easy to understand, easy to forecast, and easy to get started.

  1. Anyone can get started for free
  2. Manually synced data flows are free. You can try all of the connectors without paying a dime
  3. Scheduled data flows have simple to understand FIXED PRICES with UNLIMITED DATA VOLUMES
  4. You can pay monthly, or annually, and cancel any time

Now, let's talk about BigQuery.

BigQuery Data Ingestion

BigQuery is a serverless, scalable, fully managed cloud data warehouse that's part of the Google Cloud Platform (GCP).

Data warehouses are great platforms on which to store information, build data models, and run compute to analyze your data; however, most data teams care less about the infrastructure and more about the value they can generate for the business with a tool like BigQuery.

BigQuery Use Cases

There are three main ways to create value with a data warehouse.

  1. Analytics – This is the most common use case for a tool like BigQuery. Data engineering teams will centralize all of their data into a warehouse to then write SQL and build dashboards. In most scenarios, the data being analyze is 1st party data, but at times, teams will use data sets from partners or third party data providers.
  2. Process Automation – Every organization has workflows that need to be streamlined. In most scenarios these use cases are closer to real-time, and business value is created by removing manual steps from the process.
  3. Product Development – Product development is the most concrete form of value creation, but also typically the largest investment. In these scenarios, data teams look a lot like product and engineering organizations. By using data transformation to convert raw data into products for clients, teams are able to generate direct revenue from their endeavors.

Your Options for BigQuery ETL

With the advent of cloud data warehousing (tools like BigQuery), and the decoupling of data replication (the EL in ELT) and data transformation (with tools like DBT Labs, Coalesce.io and Narrator), ETL is simpler than ever.

If you are just getting started with ETL and your need your product database, your CRM system, or your HRIS system connected to BigQuery, RudderStack can be a great choice.

When you need to connect business unit specific business applications to BigQuery, Portable offers over 300+ data connectors to make your life simple. We'll even build new data sources at no cost to you.

Ready to get started? Sign Up For Portable Today!

Pricing is simple, predictable, and based on connectors instead of data volume. Data is loaded into ready-to-query schemas so you can start building in minutes.

It's free to sign up and start moving data to BigQuery.