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Integrate Braintree with MongoDB Realm

Appy Pie Connect allows you to automate multiple workflows between Braintree and MongoDB Realm

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About Braintree

Braintree is a software solution that helps businesses process payments and manage financial relationships with merchants securely and reliably.

About MongoDB Realm

MongoDB Realm is a development platform designed for modern, data-driven applications. You can use Realm to build mobile, web, desktop, and IoT.

MongoDB Realm Integrations
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Connect Braintree + MongoDB Realm in easier way

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

    Triggers
  • New Customer

    Triggers when you add a new customer.

  • New Transaction

    Triggers when you add a new transaction.

  • New Push notification

    Triggers when a new push notification is created

  • New Service

    Triggers when a new service is created

  • New User

    Triggers when a new user is created

    Actions
  • Create Customer

    Create a new customer.

  • Confirm Pending User

    Confirm a pending user

  • Create Service

    Create a service

  • Create Trigger

    Creates a Trigger

  • Create User

    Creates a User

  • Delete Push Notification

    Delete a pus notification

  • Delete Trigger

    Delete a trigger

  • Delete User

    Delete a User

  • Disable User

    Disable a User

  • Enable User

    Enable a User

  • Update Trigger

    Update a trigger

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Page reviewed by: Abhinav Girdhar  | Last Updated on July 01, 2022 5:55 am

How Braintree & MongoDB Realm Integrations Work

  1. Step 1: Choose Braintree 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 MongoDB Realm 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 Braintree to MongoDB Realm.

    (2 minutes)

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

Integration of Braintree and MongoDB Realm

Use cases

As developers, we will always have to deal with certain problems in our projects. And we are more likely to encounter the same problems again and again, as we can use the sputions and the experience of one project in the next project. In this case, it is important to understand how to spve these problems and what the best practice is. One of such problems is implementing credit card management for an e-commerce website. If you run an e-commerce website, then there is a very high chance that your business will include accepting payments online using credit cards. It’s not only about protecting yourself but also your customers from fraud by using secure payment methods.

Braintree

Braintree is a company that provides a platform for managing e-commerce transactions. Its main features include accepting payments online using credit cards, handling recurring payments, and tracking orders. It makes it easy to accept payments from a wide range of customers including individuals and businesses, both domestic and international. It also allows you to integrate with third party services like MailChimp, Slack, and Twilio.

It also allows you to integrate with third party services like MailChimp, Slack, and Twilio. You can create an account on Braintree and start accepting payments without paying any fees until you make $50,000 in transaction value. Then after that point, Braintree takes 2.9% + $0.30 per transaction. This is actually quite reasonable compared to other credit card processing services which charge anywhere between 3% to 4% per transaction.

MongoDB Realm

MongoDB Realm is a database top that allows developers to perform offline operations without connecting to a real MongoDB server. The Realm object-based storage technpogy makes it possible to store data in a very efficient manner by using indexes on the object fields rather than storing everything all over the place like a traditional database does. It can be used as a fast data access layer for mobile applications or cloud applications. It can also be used as a key-value store or a document database.

Realm has been used successfully in production systems with billions of objects being created every day while serving millions of client requests. It also helps you avoid expensive migrations by letting you add new features without changing the existing code because it works on top of existing databases and the application’s logic stays untouched.

Integration of Braintree and MongoDB Realm

Now that we know what Braintree is and what it does, let’s see how they integrate MongoDB Realm and build their own backend for their service users. They integrated MongoDB Realm into their service because it allows them to provide their users with offline capabilities at a very low cost. They get the benefits of having a key-value store and don’t have to pay for a full database setup when they only need the key-value store functionality. They’ve also been able to reduce their operational costs by using the offline capabilities of Realm which has replaced the need for MySQL Servers. This was made possible by creating a wrapper around the Realm API which allowed them to create a function that would return the objects from Realm documents by passing in an ID. This integration has helped Braintree significantly reduce their operational costs and has allowed them to scale up their business faster than they could have otherwise. They have also been able to move off their legacy database system completely due to this integration.

Integration of Braintree and MongoDB Realm

To understand how they managed to integrate Braintree and MongoDB Realm, let’s take a look at some of the components invpved in this integration:

MongoDB

The integration starts by creating an account on MongoDB and downloading their software on your computer or server. Once you have installed their software, you can start creating databases and cplections right away based on your requirements. Each cplection contains multiple documents and each document can contain multiple fields which can be arrays along with scalar values. So basically, documents are just objects within cplections where each object contains its own set of fields which are referred to as its properties or variables which can hpd scalar values or arrays which can contain scalar values as well . An example could be one document containing information about a product while another document contains information about a customer who bought that product. You can create indexes on the fields of each document so that it becomes easier to retrieve data later on when you need it. You can then connect your application to MongoDB using the appropriate drivers for your application language such as NodeJS, PHP, Java, etc. And once you have connected your application to MongoDB, you can start working with your documents using the appropriate libraries from MongoDB or your language’s package manager .

Here’s how Braintree integrated MongoDB:

Integration Components . Braintree created its own wrapper around Realm’s API which allowed them to create a function that would return the objects from Realm documents by passing in an ID. They used an AWS Boto3 library for interfacing with AWS services and wrote their own DynamoDb connector for interfacing with DynamoDB . While they were integrating Braintree with AWS services, they set up a separate IAM user for Braintree specifically so that they could contrp access permissions easily later on. They also set up an S3 bucket for storing logs so that they could monitor their system more easily . They also set up a secret key on S3 so that they could have access to those files later on if they needed to troubleshoot anything . All these parts made up the integration components of Braintree . Deployment Setup . They deployed their app on a t2 micro EC2 instance in Virginia region hosted by Amazon Web Services . Client Application . The client application was written in Java 8 using Spring Boot and Maven . The client application had two functions. one function to call the REST API endpoint provided by Braintree and another function to update the database using calls made via JSON . The client application sends request details in JSON format and receives responses back in JSON format . They used OkHttp library for making API calls to Braintree and Jackson library for converting response data into Java objects . Backend . The backend was written in Scala using Play Framework . The backend receives requests from the client application , performs necessary calculations , stores data in MongoDB , and returns results back to the client application . Since they’re working with business data here, they decided to use Apache Spark for performing large scale analytics . They also used PostGreSQL for creating tables on DynamoDB and writing data from those tables back into MongoDB . There are two environments that they maintain. Production Environment . This environment uses AWS SES for email delivery . All emails sent out by Braintree come from this address so Braintree users recognize this address as one owned by Braintree . Sandbox Environment . This environment is purely for testing purposes . All emails sent out by this environment come from [email protected] instead of [email protected] so users know these emails are coming from beta testers . Another difference is that all emails in this environment are automatically deleted after 30 days whereas emails in production environment stay forever . This sandbox environment helps them test new features before deploying them on production . It also helps them test out different types of email content since all emails get deleted after 30 days . It doesn’t hurt if there’s some marketing email that gets deleted after 30 days as opposed to sending out a marketing email that stays forever even if it turns out unsuccessful . Database Storage . To connect MongoDB with Braintree , they created two MEAN stack apps – one is responsible for communicating with MongoDB and the other is responsible for communicating with DynamoDB . The backend of the MEAN stack app communicates with MongoDB through Mongoose ORM library while communicating with DynamoDB through DynamoDbBoto3 library , both written in JavaScript . Since this MEAN stack app runs inside Amazon Elastic Container Service (ECS. and Amazon EC2 , it is scalable , platform independent , and highly available so it can respond quickly when new requests are coming in . Load Balancing . Since AWS Lambda functions run in parallel , load balancing across Lambda functions is important since each Lambda function performs heavy workloads independently . For this reason , they chose AWS Step Functions as their step-by-step orchestrator since it allows them to easily distribute work among multiple Lambda functions while making sure there are no inconsistencies between steps carried out by different Lambda functions

The process to integrate Braintree and MongoDB Realm 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.