Differences between Amazon S3 and S3n in Hadoop

Question

I do not understand the differences between using S3 and S3n with my Hadoop cluster, can someone explain?

Answer 1

Amazon Simple Storage Service (Amazon S3) is a storage service that offers, data availability, security, scalability, and high performance. This means customers with all sizes(huge or tiny) and industries get the flexibility to store and protect any amount of data for different use cases, such as websites, backup and restore, archive, mobile applications, big data analytics, etc.

s3n and s3 are two file Systems used for using Amazon S3

• s3(S3 Block FileSystem) is a block-based file-system backed by Amazon S3. Here, files are stored in blocks, just like HDFS. This filesystem requires you to dedicate a bucket for the filesystem - you are not allowed to write other files to the pre-existing buckets containing files. In this filesystem, the storing capacity of files can be greater than 5GB, but the limitation is that they will be interoperable with other S3 tools.

• s3n is an object-based file system that comes with a size is the concern, where the file size is limited up to 5 GB.

s3n(S3 Native FileSystem) is a native filesystem for reading and writing regular files on S3. Here, the only advantage as compared to s3 is that you can access files that were written with other tools on AmazonS3.

If you want to get more information regarding the same, refer the following video: