Build a secure data lake in days instead of months. Our experience working with tens of thousands of customers to build productive data lakes has allowed us to make every aspect of analyzing data in the cloud easier. For example, AWS Lake Formation automates the manual steps required to build a data lake and provides a single security mechanism across all of your data, so you spend less time on the undifferentiated heavy lifting required to build a data lake and more time exploring your data to get answers to your most important questions.

AWS is the fastest and most cost-effective place to store and analyze data. For example, Amazon S3 provides five storage classes and automatic data lifecycle management so you pay only what’s needed for your data based on how that data is used. Amazon Redshift is 3x faster than any other cloud data warehouse and gets faster every year. Amazon EMR provides the fastest place to run Apache Spark and Apache HIVE workloads in the cloud. EMR’s deep integration with the rest of AWS makes it easy to take advantage of cost-saving features, such as EC2 Spot instances, to reduce costs by up to 90%.

Having all your data locked in a single siloed analytics service doesn’t work anymore. Modern analytics requires a collection of different tools and approaches, including SQL, R, Scala, Jupyter, and Python, to get to the right insights and answers using a variety of languages. AWS provides a mature and comprehensive set of analytics services that run against the open data lake so you can use the right tool for the right job without needing to move or transform data for each different analytics approach. All of our services support accessing data stored in a single object store (S3) with open APIs, in open formats (eg: Apache Paquet, Apache ORC, Apache Avro), and using both proprietary (Redshift for data warehousing) and open engines (eg: Spark, Hive). 

Keeping your data secure and complying with relevant regulations is essential. AWS provides a comprehensive set of tools that goes beyond standard security functionality like encryption and access control to pro-active monitoring and unified management of security policies. For example, Amazon Macie helps monitor your data lake to ensure you are not accidentally exposing credentials or personally identifiable information (PII). Amazon Inspector helps to enforce best practices and identify configuration issues that could be exploited, and AWS Lake Formation allows you to consistently control access to data in your data lake across all analytics services. 

Amazon S3 is secure, highly scalable, durable object storage with millisecond latency for data access. S3 is built to store any type of data from anywhere – web sites and mobile apps, corporate applications, and data from IoT sensors or devices. It is built to store and retrieve any amount of data, with unmatched availability, and built from the ground up to deliver 99.999999999% (11 nines) of durability. S3 Select focuses data read and retrieval, reducing response times up to 400%. S3 provides comprehensive security and compliance capabilities that meet even the most stringent regulatory requirements.  

Amazon Glacier is secure, durable, and extremely low cost storage for long-term backup and archive that can access data in minutes, and similarly Glacier Select reads and retrieves only the data needed. It is designed to deliver 99.999999999% durability (11 nines), and provides comprehensive security and compliance capabilities that can help meet even the most stringent regulatory requirements. Customers can store data for as little as $0.004 per gigabyte per month, a significant savings compared to on-premises solutions.

AWS Glue is a fully managed service that provides a data catalog to make data in the data lake discoverable, and has the ability to do extract, transform, and load (ETL) to prepare data for analysis. The data catalog is automatically created as a persistent metadata store for all data assets, making all of the data searchable, and queryable in a single view.