Amazon Web Services Cloud
AWS Management Console
AWS Command Line Interface
Software Development Kits
Analytics
Amazon Athena
It's an interactive query service making it easy to analyze data in Amazon S3 with the help of standard SQL and does not require any infrastructure to manage as Athena is serverless and you only pay for the queries you run.
Athena is easy to use and does not require any kind of complex extract, transform, and load (ETL) jobs in order to prepare your data for analysis which makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.
It's an out-of-the-box integrated with AWS Glue Data Catalog, which helps you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new as well as modified table and partition definitions, and maintain schema versioning.
Amazon CloudSearch
Amazon Elasticsearch Service
Amazon EMR
Amazon FinSpace
FinSpace can remove the heavy lifting of building and maintaining a data management system for financial analytics and you can easily share as well as discover data across your organization according to your compliance requirements. It also contains a library with 100+ functions, such as time bars and Bollinger bands, for you to prepare data for analysis.
Amazon Kinesis
Amazon Redshift
It's one of the most widely used cloud data warehouse which is fast, simple, and cost-effective for analyzing all your data with the help of standard SQL as well as your existing Business Intelligence (BI) tools. Here you can run complex analytic queries against terabytes to petabytes of structured and semi-structured data using sophisticated query optimization, columnar storage on high-performance storage, and massively parallel query execution.
Amazon QuickSight
AWS Data Exchange
AWS Data Pipeline
It's a type of web service that can reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specific intervals. It helps you to easily create complex data processing workloads that are fault tolerant, repeatable, and highly available without even have to worry about ensuring resource availability, managing inter-task dependencies, retrying transient failures or timeouts in individual tasks, or creating a failure notification system. AWS Data Pipeline also helps you to move and process the data that was previously locked up in on-premises data silos.
AWS Glue
It's a fully managed Extract, Transform, and Load (ETL) service which is easier for the customers to prepare as well as load their data for analytics. You just have to point AWS Glue to the data stored on AWS so that it can discover your data to store the associated metadata in the AWS Glue Data Catalog. Once cataloged, your data can be instantly searchable, queryable, and available for ETL.
AWS Lake Formation
This service allows you to easily set up a secure data lake in days which is a centralized, curated, and secured repository that can store all your data, both in its original form and prepared for analysis. It enables you to break down data silos and combine various analytics to gain insights and guide better business decisions.
It is as simple to create a data Lake Formation as defining where your data is located as well as what data access and security policies you want to apply. Lake Formation collects as well as catalogs data from databases and object storage, moves them to into your new Amazon S3 data lake, cleans and classifies it with the help of machine learning algorithms, and secure access to your sensitive data. Users can leverage these data sets according to their choice of analytics and machine learning services, such as Amazon EMR for Apache Spark, Amazon Redshift, Amazon Athena, SageMaker, and Amazon QuickSight.
Amazon Managed Streaming for Apache Kafka (Amazon MSK)
It's a fully managed service that allows you to easily build as well as run applications that use Apache Kafka to process streaming data which is an open-source platform for building real-time streaming data pipelines and applications. You can use Apache Kafka APIs with the help of Amazon MSK, to populate data lakes, stream changes to and from databases, and power machine learning and analytics applications.
You can create highly available Apache Kafka clusters on Amazon MSK console with settings as well as configuration based on Apache Kafka's deployment best practices. Amazon MSK can automatically provision as well as run your Apache Kafka clusters while also continuously monitoring cluster health and automatically replacing unhealthy nodes with no downtime to your application; besides it can also protect your Apache Kafka cluster by encrypting the data at rest.
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