Understanding AWS Big Data Services available in the Cloud

Amazon Web Services is the cloud platform which allows you to handle the Big Data. Whether it is structured or unstructured data, AWS enables you to collect, store, process, analyze and visualize Big Data on the cloud. Irrespective of the three V’s (Volume, Velocity and Variety) of the Big Data, you can build any application and support any type of workload.

There are many Amazon Web Services that are available for Cloud users to manage and use their Big Data. The most widely used services are Amazon Elastic MapReduce (Amazon EMR), Amazon Kinesis, Amazon S3, Amazon Redshift, and Amazon DynamoDB.

Amazon Elastic MapReduce (EMR)

Amazon Elastic Map Reduce

Amazon Elastic MapReduce (Amazon EMR) is a web service that makes it easy to quickly and cost-effectively process vast amounts of data.

Amazon EMR uses Hadoop, an open source framework, to distribute your data and processing across a resizable cluster of Amazon EC2 instances. Amazon EMR is used in a variety of applications, including log analysis, web indexing, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics. Customers launch millions of Amazon EMR clusters every year.

 

Amazon KinesisAmazon Kinesis

 

Amazon Kinesis is a fully managed service for real-time processing of streaming data at a massive scale. You can use it to collect and process hundreds of terabytes of data per hour from hundreds of thousands of sources in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation, social media, and others.

Your applications can respond to changes in your data stream in seconds, at any scale, while only paying for the resources you use. You can build real-time dashboards, capture exceptions and generate alerts, drive recommendations, and make other real-time business or operational decisions. You can also easily send data to a variety of other services such as Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, or Amazon Redshift.

 

Amazon S3

AmaAmazon S3zon S3 is storage for the Internet and is also fundamental building block in all big data architectures on AWS. It is designed to make web-scale computing easier for developers.

Amazon S3 provides a simple web-services interface that can be used to store and retrieve any amount of data, at any time, from anywhere on the web. It gives any developer access to the same highly scalable, reliable, secure, fast, inexpensive infrastructure that Amazon uses to run its own global network of web sites. The service aims to maximize benefits of scale and to pass those benefits on to developers.

 

Amazon Redshift

Amazon Redshift

Amazon Redshift is a fast, fully managed, petabytes-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. You can start small for just $0.25 per hour with no commitments or upfront costs and scale to a petabytes or more for $1,000 per terabyte per year, less than a tenth of most other data warehousing solutions.

 

Amazon Dynamo DB

DynamAmazon Dynamo DBoDB is a fast, fully managed NoSQL database service that makes it simple and cost-effective to store and retrieve any amount of data, and serve any level of request traffic. Its reliable throughput and single-digit millisecond latency make it a great fit for gaming, ad tech, mobile and many other applications.

DynamoDB makes it simple and cost-effective to store and retrieve any amount of data, and serve any level of request traffic. All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability.

 

Drop mail at info@sysfore.com or call us at +91-80-4110-5555, and our Sysfore Amazon Cloud experts will get back to you.

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>