How to Move Data from MongoDB to Amazon S3 in Parquet

Customer-facing analytics has become a crucial feature for Software as a Service (SaaS) products, offering insights to end customers as part of the product experience. To effectively analyze data, it may be necessary to move data from operational databases like MongoDB to scalable and cost-effective data storage services such as Amazon S3. Parquet, a columnar storage file format, is particularly suitable for this data transfer pipeline due to its efficient data compression and encoding schemes that result in reduced storage space and improved query performance. In this tutorial, you'll learn how to set up a data pipeline to move data from MongoDB to Amazon S3 in Parquet format using MongoDB Atlas's Data Federation feature. This method leverages MongoDB's existing Atlas infrastructure, allowing for querying and transforming data before exporting it to S3 and automating data movement based on event triggers. The tutorial also explores manual, one-time migrations and automated, continuous migrations for moving data from MongoDB to Amazon S3 in Parquet format. To successfully move data from MongoDB to Amazon S3, you'll need a MongoDB Atlas account, a MongoDB cluster with sample data sets, the AWS CLI installed and configured, two new Amazon S3 buckets, and the MongoDB Shell installed. The tutorial guides you through setting up the necessary environments, creating an AWS IAM role and an S3 bucket access policy, connecting the MongoDB data federation instance with a MongoDB database and Amazon S3 buckets, moving the data once, and setting up a continuous pipeline for future data.