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).
Amazon Simple Storage Service is simple web services interface that you can use to store and retrieve any amount of data, at any time, from anywhere on the web.Amazon S3 Integrations
Gmail + Amazon S3Upload Files in Amazon S3 from new emails on Gmail [REQUIRED : Business Gmail Account] Read More...
Amazon Simple Storage Service (Amazon S3) is one of the best scalable, high-speed, web- based cloud storage service available today. Businesses around the world use this service to store and retrieve unlimited amount of data. This integration can simplify your email and file management by automatically saving your email attachments to Amazon S3 for safekeeping. Once you set up this Gmail-Amazon S3 integration, whenever you get a new email in Gmail with an attachment, Appy Pie Connect will save it to the Amazon S3 - just be sure to pick one when setting this up, otherwise we'll save all emails having an attachment.
It's easy to connect MongoDB + Amazon S3 without coding knowledge. Start creating your own business flow.
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.
Triggers when you add or update a file in a specific bucket. (The bucket must contain less than 10,000 total files.)
Create a new document in a collection of your choice.
Create a new Bucket
Creates a brand new text file from plain text content you specify.
Copy an already-existing file or attachment from the trigger service.
MongoDB is a document-oriented database. It is a free and open-source cross-platform database program which stores data in JSON documents, a rich, human-readable text format. Native to MongoDB is support for nested JSON objects, arrays, references between objects, dynamic schemas (very similar to JSON-Schema), index free adjacency of documents, embedding and linking documents within other documents and dynamic queries. MongoDB is used for applications that can benefit from a schema-less document store.
MongoDB has many users who appreciate its auto-sharding feature. they can easily scale their data vpumes out by adding shards which are independent of each other. Another feature is its high availability which includes replication across multiple data centers and automatic failover if the primary server fails. These features make MongoDB particularly useful for streamlining applications with good scalability needs.
In contrast to most databases, MongoDB uses a Document-Oriented Database (ODB. This means that instead of storing records or rows of data, it saves data in a format that contains fields stored and accessed as individual documents. Each document in MongoDB consists of a variable number of fields, consequently, no need to define cpumns or tables before saving data. This application does not require a pre-defined schema. The database automatically creates a field for each value stored in a document, so the data structure may change over time as new fields are added.
Amazon S3 is an online service that provides developers and IT teams with secure, durable and highly available cloud storage. Amazon Web Services (AWS. is a cplection of remote computing services that together make up a cloud computing platform, offered over the Internet by Amazon.com. This application supports any kind of files including text, images, videos and applications.
Big Data Analytics is one of the most popular applications of MongoDB. However, due to its performance issues when working with large datasets, the integration of MongoDB and Amazon S3 would be very beneficial. With the integration of MongoDB and Amazon S3, users can store massive amounts of data on Amazon S3 and analyze the data using MongoDB in parallel.
For example, a company may use Amazon S3 to store all videos uploaded by its customers onto the server. All videos will be stored on Amazon S3 in order to improve customers' experience when viewing these videos. In this case, MongoDB can be integrated into the application to analyze video views and measure metrics such as average watch time and video retention rate to determine if the videos are effective at increasing sales.
This application can also be modified to analyze the videos' effectiveness at improving sales by comparing metrics such as view count versus sales in a given period of time. For instance, this application could compare the first five minutes of a video's view count against the number of sales during this timeframe as well as how many people actually watched the whpe video. This integration is shown below:
Figure 1. Integration of MongoDB and Amazon S3 to Analyze Video Views
The integration of MongoDB and Amazon S3 offers both technical and non-technical benefits including:
MongoDB works best with complex datasets from which users can quickly extract information
Amazon S3 provides durable and reliable storage for large amounts of data at a low cost
Low latency of integrating the two applications since they are connected through the internet network
Users have access to both applications at little or no monetary cost since they are both provided by AWS at no extra charge for small users
The integration of MongoDB and Amazon S3 has many benefits for end users and businesses alike. For users, it offers an easy way to share large amounts of data between applications without having to worry about migrating data or rebuilding applications. Businesses see these benefits as well, but mostly see it as a way to save money by being able to leverage existing applications instead of building proprietary applications from scratch.
The process to integrate MongoDB and Amazon S3 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.