Amazon S3 (Simple Storage Service) is based in the cloud and is an optimized data storage service that stores data in its native form regardless of whether it is in unstructured, semi-structured, or structured format. Data durability of S3 is as high as 99.999999999 (11 9s) and data is stored in fully safe and secured environment irrespective of the volume.

Functioning of Amazon S3 and its use in building S3 data lake

Before going into the intricacies of building an S3 data lake it is necessary to understand the functioning of Amazon S3. In this service, data files containing metadata and objects are stored in buckets and for uploading metadata or files, the object has to be uploaded to Amazon S3. Once this step is gone through, permissions can be set in on the metadata or the related objects stored in the buckets (containers). Selected personnel is accorded access to these buckets and only they can decide where the logs and objects will be stored on Amazon S3.

When an S3 data lake is built on Amazon S3, many competencies can be used. The main ones are media data processing applications, Artificial Intelligence (AI), Machine Learning (ML), big data analytics, and high-performance computing (HPC). When all these come together, organizations get access to critical and incisive business intelligence and analytics from S3 data lake as well as unstructured data sets.

The main benefits of Amazon S3 Data Lake

S3 data lake offers several benefits and is the reason why most organizations are choosing S3 to build their data lakes. A few of them are given here.

• In the past, storage and computing facilities were closely interlinked, making it almost impossible to individually estimate the costs of data processing and storage and infrastructure maintenance. The advantage with S3 data lake is that computing and storage are in different silos and data of all types and formats can be stored in their native formats at affordable costs.

• On S3 data lake, users get access to the services of Amazon S3 for serverless computing where codes can be run without having to manage or provision servers. Data processing, querying, and implementation can be done on both serverless and non-cluster Amazon Web Service platforms like Amazon Athena, Amazon Rekognition, Amazon Redshift Spectrum, and AWS Glue. Payment is only for the quantum of storage and computing resources used without any flat or one-time fees.

• Several third-party vendors support the APUs of the Amazon S3 data lake. The most used and user-friendly ones are Amazon Hadoop and other similar analytics suppliers. This tool can be used easily on the Amazon S3 data lake.

These are some of the cutting-edge features and capabilities of the S3 data lake that make it stand out among the traditional data lakes. It is also why Amazon S3 data lake is the most-used service for the modern business environment.