How to load data from Google Ads to MongoDB

Learn how to use Airbyte to synchronize your Google Ads data into MongoDB within minutes.

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Set up a Google Ads connector in Airbyte

Connect to Google Ads or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up MongoDB for your extracted Google Ads data

Select MongoDB where you want to import data from your Google Ads source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Google Ads to MongoDB in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Google Ads as a source connector (using Auth, or usually an API key)
set up MongoDB as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Google Ads

The Google Ads API is the modern programmatic interface to Google Ads and the next generation of the AdWords API and it is a paid online advertising platform offered by Google. Google Ads is a paid search channel. Google Ads is a key digital marketing tool for any business which is looking to get meaningful ad copy in front of its target audience. Google AdWords is a well known marketplace where companies pay to have their website ranked at the top of a search results page, based on keywords.

What is MongoDB

MongoDB is a database that powers crucial applications and systems for global businesses. Designed for developers and specializing in the areas of open source, software development, and databases, it offers functionality such as horizontal scaling, automatic failover, and the capability to assign data to a location.

Integrate Google Ads with MongoDB in minutes

Try for free now

Prerequisites

A Google Ads account to transfer your customer data automatically from.
A MongoDB account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Google Ads and MongoDB, for seamless data migration.

When using Airbyte to move data from Google Ads to MongoDB, it extracts data from Google Ads using the source connector, converts it into a format MongoDB can ingest using the provided schema, and then loads it into MongoDB via the destination connector. This allows businesses to leverage their Google Ads data for advanced analytics and insights within MongoDB, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Google Ads as a source connector

1. Go to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.

2. Click on the "New Source" button and select "Google Ads" from the list of available connectors.

3. Enter a name for your connector and click on "Next".

4. Enter your Google Ads credentials, including your client ID, client secret, refresh token, and developer token.

5. Click on "Test Connection" to ensure that your credentials are correct and that Airbyte can connect to your Google Ads account.

6. Once the connection is successful, select the accounts that you want to sync with Airbyte.

7. Choose the sync mode that you want to use, either "Full Refresh" or "Incremental".

8. Set the frequency of your sync and click on "Create Source" to save your settings.

9. Your Google Ads source connector is now set up and ready to use. You can view your data in the Airbyte dashboard and start syncing it with your destination.

Step 2: Set up MongoDB as a destination connector

Step 3: Set up a connection to sync your Google Ads data to MongoDB

Once you've successfully connected Google Ads as a data source and MongoDB as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Google Ads from the dropdown list of your configured sources.
Select your destination: Choose MongoDB from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Google Ads objects you want to import data from towards MongoDB. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Google Ads to MongoDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your MongoDB data warehouse is always up-to-date with your Google Ads data.

Use Cases to transfer your Google Ads data to MongoDB

Integrating data from Google Ads to MongoDB provides several benefits. Here are a few use cases:

Advanced Analytics: MongoDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Google Ads data, extracting insights that wouldn't be possible within Google Ads alone.
Data Consolidation: If you're using multiple other sources along with Google Ads, syncing to MongoDB allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Google Ads has limits on historical data. Syncing data to MongoDB allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: MongoDB provides robust data security features. Syncing Google Ads data to MongoDB ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: MongoDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Google Ads data.
Data Science and Machine Learning: By having Google Ads data in MongoDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Google Ads provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to MongoDB, providing more advanced business intelligence options. If you have a Google Ads table that needs to be converted to a MongoDB table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Google Ads account as an Airbyte data source connector.
Configure MongoDB as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Google Ads to MongoDB after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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How to Sync Google Ads to MongoDB Manually

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FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Google Ads?

What data can you extract from Google Ads?

Google Ads API provides access to a wide range of data related to advertising campaigns, including:

- Campaigns: Information about the campaigns, such as name, status, budget, and targeting settings.

- Ad groups: Details about the ad groups, including name, status, and targeting criteria.

- Ads: Information about the ads, such as type, format, and performance metrics.

- Keywords: Data related to the keywords used in the campaigns, including search volume, competition, and performance metrics.

- Bidding: Details about the bidding strategies used in the campaigns, such as manual bidding or automated bidding.

- Conversions: Information about the conversions generated by the campaigns, including conversion rate, cost per conversion, and conversion tracking settings.

- Audience: Data related to the audience targeting used in the campaigns, such as demographics, interests, and behaviors.

- Location: Information about the geographic targeting used in the campaigns, including location targeting settings and performance metrics.

Overall, the Google Ads API provides a comprehensive set of data that can be used to optimize advertising campaigns and improve their performance.

How do I transfer data from Google Ads?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up Google Ads to MongoDB as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Google Ads to MongoDB and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

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Databases

Marketing Analytics

How to load data from Google Ads to MongoDB

Learn how to use Airbyte to synchronize your Google Ads data into MongoDB within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

Step 1: Setup Google Ads

Step 2: Setup MongoDB

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Google Ads and MongoDB

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Google Ads as a source connector (using Auth, or usually an API key)
set up MongoDB as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Google Ads

What is MongoDB

Integrate Google Ads with MongoDB in minutes

Try for free now

Prerequisites

A Google Ads account to transfer your customer data automatically from.
A MongoDB account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Step 1: Set up Google Ads as a source connector

1. Go to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.

2. Click on the "New Source" button and select "Google Ads" from the list of available connectors.

3. Enter a name for your connector and click on "Next".

4. Enter your Google Ads credentials, including your client ID, client secret, refresh token, and developer token.

5. Click on "Test Connection" to ensure that your credentials are correct and that Airbyte can connect to your Google Ads account.

6. Once the connection is successful, select the accounts that you want to sync with Airbyte.

7. Choose the sync mode that you want to use, either "Full Refresh" or "Incremental".

8. Set the frequency of your sync and click on "Create Source" to save your settings.

9. Your Google Ads source connector is now set up and ready to use. You can view your data in the Airbyte dashboard and start syncing it with your destination.

Step 2: Set up MongoDB as a destination connector

Step 3: Set up a connection to sync your Google Ads data to MongoDB

Once you've successfully connected Google Ads as a data source and MongoDB as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Google Ads from the dropdown list of your configured sources.
Select your destination: Choose MongoDB from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Google Ads objects you want to import data from towards MongoDB. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Google Ads to MongoDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your MongoDB data warehouse is always up-to-date with your Google Ads data.

Use Cases to transfer your Google Ads data to MongoDB

Integrating data from Google Ads to MongoDB provides several benefits. Here are a few use cases:

Advanced Analytics: MongoDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Google Ads data, extracting insights that wouldn't be possible within Google Ads alone.
Data Consolidation: If you're using multiple other sources along with Google Ads, syncing to MongoDB allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Google Ads has limits on historical data. Syncing data to MongoDB allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: MongoDB provides robust data security features. Syncing Google Ads data to MongoDB ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: MongoDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Google Ads data.
Data Science and Machine Learning: By having Google Ads data in MongoDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Google Ads provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to MongoDB, providing more advanced business intelligence options. If you have a Google Ads table that needs to be converted to a MongoDB table, Airbyte can do that automatically.