Amazon SQS is a fully managed message queuing service. It offers reliable, highly scalable, reliable messaging and transaction processing that lets you decouple tasks or processes that must communicate.
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).MongoDB Integrations
Gmail + Amazon SQSCreate Amazon SQS JSON messages for emails matching search term on Gmail [REQUIRED : Business Gmail Account] Read More...
If you use email content to create an Amazon SQS message, then this integration is for you. Once you set up this Gmail-Amazon SQS integration, it will trigger every time a new email matching your search term is received in your Gmail account, instantly adding a new JSON message to Amazon SQS to ensure that your pipeline is always moving. With Appy Pie Connect, you can set up this integration without writing a single line of code.
Note: To use this integration you must have a Business Gmail account.
It's easy to connect Amazon SQS + MongoDB without coding knowledge. Start creating your own business flow.
Triggers when you add a new queue
Triggers when you add a new collection.
Triggers when you add a new database.
Triggers when you add a new document to a collection.
Triggers when you add a new field to a collection.
Create a new JSON message using data from the source trigger
Create a new message.
Create a new queue
Create a new document in a collection of your choice.
Amazon Simple Queue Service (Amazon SQS. is a distributed and highly available message queuing service provided by Amazon. It is used to send messages between microservices or distributed components in the cloud. Amazon SQS provides a scalable, reliable, fast, and cost-effective messaging spution across all major AWS regions.
MongoDB is an open source database that stores data in JSON-like documents, instead of tables. This document-oriented approach makes it easier for developers to work with data in MongoDB than in a relational database. In addition, MongoDB has a rich set of features that include high availability, auto-sharding, replication, and a global load balancing system. MongoDB is one of the most popular NoSQL databases and supports programming languages such as Java, PHP, Ruby, C# and Python.
Let’s consider an example where we have a website where users can post reviews of books they have read. The system needs to store this information so that other users can easily find out what other users thought about a book they are thinking about reading. In this scenario, the Amazon SQS queue acts as a buffer which stores the messages from clients and processes them according to priority. Also, the microservices can be written in any programming language that supports Amazon SQS (such as Java, Node.js, Python etc.)
The diagram below shows an overview of the integration between Amazon SQS and MongoDB:
In this scenario, we are using two different services. 1. Amazon SQS 2. MongoDB
Integrating these services allows us to retain the form of the data in our application. We can also add or remove services whenever necessary without having to worry about data consistency since both services are able to handle data integrity on their own.
The system has three main components. 1. Client App 2. Microservice 3. Database(Amazon SQS and MongoDB)
The client app connects to our website’s server via HTTP. On the other hand, our microservice connects to an Amazon SQS queue while the database connects to MongoDB. The client app sends a request to our website’s server through HTTP. This request contains the form data inputted by the user such as user name and email address and some information about a book that was read by the user such as book title and author. Our website’s server then sends the request to the microservice via HTTP. This request contains the form inputted by the user such as user name and email address and some information about a book that was read by the user such as book title and author. The microservice stores these requests on an Amazon SQS queue with a specified priority level. The priority level determines the order in which the microservice will process these requests once it receives them from the Amazon SQS queue. The microservice then sends a response back to our website’s server which displays it to the user. Now, let’s say that our service receives the request/response from our website’s server via HTTP. Then it reads the requested information from the appropriate location in MongoDB based on the information contained in the request/response received from our website’s server. Finally, our service sends this information back to our website’s server via HTTP which then displays it to the user via HTML content.
The process to integrate Amazon SQS and MongoDB 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.