Microsoft Azure vs Amazon Web Services – Battle Field : Part 2

Big data and analytics

AWS provide data lake services with the help of Amazon S3, Glacier, Glue and Redshift.
Amazon EMR provides a managed Hadoop framework that makes it easy, fast, and cost-effective to process vast amounts of data across dynamically scalable Amazon EC2 instances. It also supports other popular distributed frameworks such as Apache Spark, HBase, Presto and Flink and can also interact with data in other AWS data stores such as Amazon S3 and Amazon DynamoDB.
Amazon Kinesis is the streaming service on AWS that helps to collect, process, and analyze real-time, streaming data enabling timely insights and react quickly to new information.

Azure Data Lake service is a scalable data lake and analytic service for big-data analytics workloads that require to run massively parallel queries for analysis.
Azure HDInsight is a big data service, that deploys Hortonworks Hadoop on Microsoft Azure, and supports the processing of massive amount of data. It supports popular open-source frameworks such as Spark, Hive, LLAP, Kafka, Storm, R & more.
Azure Stream Analytics is a serverless scalable event processing engine that enables users to develop and run real-time analytics on multiple streams of data from sources such as devices, sensors, web sites, social media etc.
Azure Event Hubs is a Big Data streaming platform and event ingestion service that is capable of processing millions of events per second. Event Hubs can store and process events, data, telemetry produced by distributed applications and devices.

Data Migration

Amazon Snowball is a data transport service that uses physical devices to transfer very large volume, petabytes, of data in and out of the AWS Cloud, securely. It solves may challenges involved with huge volume data transfers such as high cost, transfer times and security. Moreover, It doesn’t requite to write code or even purchase any hardware to transfer your data, instead a Snowball device is shipped to you on simply creation of a job in the AWS Management Console. That device then can be used to transfer the data from your network using the Snowball Client. The Client encrypts and transfer the files to the device at very high speed. This device on return will make the date available on AWS.

Azure Import/Export service is used to securely import large amounts of data to Azure Blob storage and Azure Files by shipping disk drives to an Azure datacenter. Data from one or more disk drives can be imported either to Azure Blob storage or Azure Files. Azure Import/Export service also allows you to supply your own disk drives or use disk drives supplied by Microsoft. In case you chose to transfer data using disk drives provided by Microsoft, you can use Azure Data Box Disk to import data into Azure. Microsoft ships up to 5 encrypted solid-state disk drives (SSDs) with a 40 TB total capacity per order, to your datacenter through a regional carrier. You can quickly configure disk drives, copy data to disk drives over a USB 3.0 connection, and ship the disk drives back to Azure.

Data Orchestration

AWS Data Pipeline is a web service to reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. I provide access to data, transform and process it at scale, and also transfer the results to AWS services such as S3, RDS, DynamoDB and EMR, efficiently.

Azure Data Factory is the platform that solves orchestrate and operational challenges with big data to refine enormous volume of raw data into the useful business insights. It is a cloud-based data integration service that allows you to create data-driven workflows in the cloud for data movement and data transformation. It allows to create and schedule data-driven workflows (called pipelines) that can ingest data from disparate data stores. It can process and transform the data by using compute services such as Azure HDInsight, Hadoop, Spark, Azure Data Lake Analytics, and Azure Machine Learning.