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MongoDB + Google Ads Integrations

Appy Pie Connect allows you to automate multiple workflows between MongoDB and Google Ads

  • No code
  • No Credit Card
  • Lightning Fast Setup
About MongoDB

MongoDB is an open-source document-based database management tool that stores data in JSON-like formats. It uses flexible documents instead of tables and rows to process and store various forms of data. As a NoSQL solution, MongoDB does not require a relational database management system (RDBMS).

About Google Ads

Google Ads (formerly known as AdWords) is Google's advertising platform that allows you to run ads on Google's network of sites and partner sites. The platform offers an array of ad formats to fit virtually any business objective.

Google Ads Integrations

Best ways to Integrate MongoDB + Google Ads

  • MongoDB MongoDB

    Google Ads + MongoDB

    Create Document to MongoDB from New Campaign in Google Ads Read More...
    Close
    When this happens...
    MongoDB New Campaign
     
    Then do this...
    MongoDB Create Document
  • MongoDB MongoDB

    Google Ads + MongoDB

    Create Document to MongoDB from New Ad in Google Ads Read More...
    Close
    When this happens...
    MongoDB New Ad
     
    Then do this...
    MongoDB Create Document
  • MongoDB MongoDB

    Google Ads + MongoDB

    Create Document to MongoDB from New Ad Group in Google Ads Read More...
    Close
    When this happens...
    MongoDB New Ad Group
     
    Then do this...
    MongoDB Create Document
  • MongoDB MongoDB

    Google Ads + MongoDB

    Create Document to MongoDB from New User List in Google Ads Read More...
    Close
    When this happens...
    MongoDB New User List
     
    Then do this...
    MongoDB Create Document
  • MongoDB Google Sheets

    MongoDB + Google Sheets

    Create new rows in Google Sheets for new MongoDB documents Read More...
    Close
    When this happens...
    MongoDB New Document
     
    Then do this...
    Google Sheets Create Spreadsheet Row
    Do you want to have quick access to the data in your MongoDB documents? Set up this MongoDB-Google Sheets interface to save data from new MongoDB documents into rows in a Google Sheets spreadsheet that you choose.
    How It Works
    • A new document is created
    • Appy Pie Connect creates a new row to Google Sheets automatically.
    What You Require
    • MongoDB account
    • Google Sheets account
  • MongoDB {{item.actionAppName}}

    MongoDB + {{item.actionAppName}}

    {{item.message}} Read More...
    Close
    When this happens...
    {{item.triggerAppName}} {{item.triggerTitle}}
     
    Then do this...
    {{item.actionAppName}} {{item.actionTitle}}
Connect MongoDB + Google Ads in easier way

It's easy to connect MongoDB + Google Ads without coding knowledge. Start creating your own business flow.

    Triggers
  • New Collection

    Triggers when you add a new collection.

  • New Database

    Triggers when you add a new database.

  • New Document

    Triggers when you add a new document to a collection.

  • New Field

    Triggers when you add a new field to a collection.

  • New Ad

    Triggers when a new Ad is created in Google Ads

  • New Ad Group

    Triggers when a new ad group is created in Google Ads

  • New Campaign

    Trigger on adding new campaign.

  • New User List

    Triggers when a new user list is created.

    Actions
  • Create Document

    Create a new document in a collection of your choice.

How MongoDB & Google Ads Integrations Work

  1. Step 1: Choose MongoDB as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Google Ads as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from MongoDB to Google Ads.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of MongoDB and Google Ads

MongoDB?

MongoDB is a scalable, high performance, open source document-oriented database. It is also free and easy to use.

The document oriented design of MongoDB stores data in the form of JavaScript objects; these can be queried and updated using a rich query language and can be accessed using the cross-platform MongoDB shell interface.

Google Ads?

Google Ads is the advertising platform of Google. It is a pay per click advertising service that is used by advertisers to display ads on Google.com and affiliated websites as well as its search results pages.

It was launched initially as a beta version in September 2000 with 11 months of existence it became an official product of Google and has since then become the most widely used paid advertising network with millions of advertisers and publishers using it each month.

Integration of MongoDB and Google Ads

MongoDB can be used as a data store for Google Ads. The integration of MongoDB with Google Ads allows an advertiser to store data from multiple campaigns in a single repository which makes it easier to manage campaigns.

In addition to this, it allows users to make use of advanced analysis techniques such as machine learning and statistical modelling without having to worry about the infrastructure of the database. In addition to this, it also allows users to store their data in a method that can be easily queried by machine. This would allow the creation of machine learning algorithms that can be run on a massive scale at a low cost.

Benefits of Integration of MongoDB and Google Ads

Storage – MongoDB allows the user to store their data in a manner that does not have any limitations on the size of the database nor do they have any limits on the size of the documents stored within the database. In comparison, Google Ads only allows users to store up to 2MB worth of data within their database. In addition to this, it also allows users to store more than 1 million documents within the database whereas Google Ad imposes a limit on this as well.

MongoDB has a rich query language that allows users to perform queries that are highly complex and versatile whereas Google Ads has a set of restrictions on what can be done by a user when performing queries over their database. Data storage – MongoDB supports master-slave replication where there will be one master server that will be used to process all read/write operations while one or more slave servers will be used for read only operations; this provides redundancy for your database. This allows you to run your database in a highly available manner. In comparison, Google Ads does not support master-slave replication; however, it does support multi-datacenter replication which allows you to replicate your database across multiple locations. This ensures high availability for your database. Security – MongoDB uses authentication/authorization through BSON (binary JSON. whereas Google Ads does not provide any means of authentication/authorization Security – MongoDB provides features such as user rpes, labels and indexes which allow the user to contrp access to certain portions of their database. However, it does not use SQL injection protection which makes it vulnerable to injection attacks whereas Google Ads uses SQL injection protection which prevents users from using SQL injection attacks against it. Performance – MongoDB has the ability to handle millions of requests per second at very low latency whereas Google Ad’s performance is measured in terms of data read/write operations per second. Reliability – MongoDB uses master-slave replication whereas Google Ads does not support master-slave replication; it only supports multi-datacenter replication which allows you to replicate your data across different instances for high availability. Flexibility – MongoDB offers full support for geospatial queries which are used for gepocation features whereas Google Ads does not offer any support for geospatial queries but instead has feature based gepocation which only returns the location information if the ad request contains location parameters. Flexibility – MongoDB offers support for sharding whereas Google Ads does not offer any support for sharding; however, it supports multi-datacenter replication which allows you to replicate your data across different locations for high availability which can be considered an alternative approach to sharding for high availability. Scalability – MongoDB allows you to horizontally scale your database by adding new nodes into your cluster whereas Google Ads does not allow you to horizontally scale your database by adding new nodes into your cluster but instead allows you to scale vertically by upgrading your instance size which increases your compute power but does nothing for your storage needs because each instance comes with fixed storage capabilities according to the instance size selected by the user. Security – MongoDB uses authentication/authorization through BSON (binary JSON. whereas Google Ads does not provide any means of authentication/authorization Performance – MongoDB has the ability to handle millions of requests per second at very low latency whereas Google Ad’s performance is measured in terms of data read/write operations per second. Flexibility – MongoDB offers full support for geospatial queries which are used for gepocation features whereas Google Ads does not offer any support for geospatial queries but instead has feature based gepocation which only returns the location information if the ad request contains location parameters. Flexibility – MongoDB offers support for sharding whereas Google Ads does not offer any support for sharding; however, it supports multi-datacenter replication which allows you to replicate your data across different locations for high availability which can be considered an alternative approach to sharding for high availability. Performance – MongoDB has the ability to handle millions of requests per second at very low latency whereas Google Ad’s performance is measured in terms of data read/write operations per second. Performance – MongoDB has the ability to handle millions of requests per second at very low latency whereas Google Ad’s performance is measured in terms of data read/write operations per second. Flexibility – MongoDB offers full support for geospatial queries which are used for gepocation features whereas Google Ads does not offer any support for geospatial queries but instead has feature based gepocation which only returns the location information if the ad request contains location parameters. Flexibility – MongoDB offers support for sharding whereas Google Ads does not offer any support for sharding; however, it supports multi-datacenter replication which allows you to replicate your data across different locations for high availability which can be considered an alternative approach to sharding for high availability. Performance – MongoDB has the ability to handle millions of requests per second at very low latency whereas Google Ad’s performance is measured in terms of data read/write operations per second. Too much focus on read performance – MongoDB prioritizes read performance over write performance as writes are slow as compared to reads as writes need transaction log flushes unlike reads that can just modify memory without changing disk state too much focus on read performance – MongoDB prioritizes read performance over write performance as writes are slow as compared to reads as writes need transaction log flushes unlike reads that can just modify memory without changing disk state

The process to integrate MongoDB and Google Ads may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.