AWS Partner Network (APN) Blog

Category: Amazon Simple Storage Services (S3)

WANdisco-AWS-Partners

WANdisco Accelerates GoDaddy’s Hadoop Cloud Migration to AWS Without Business Interruption

Advances in migration technology enable you to migrate data from actively-used Hadoop environments at scale to the cloud. You can benefit from AWS managed services, pace of innovation, and improve costs for your largest and most complex analytic workloads. Learn how GoDaddy migrated data from their 800-node, 2.5 PB production Apache Hadoop cluster to Amazon S3 using WANdisco’s LiveData Migrator product.

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Dremio-AWS-Partners

Using Dremio for Fast and Easy Analysis of Amazon S3 Data

Although many SQL engines allow tools to query Amazon S3 data, organizations face multiple challenges, including high latency and infrastructure costs. Learn how Dremio empowers analysts and data scientists to analyze data in S3 directly at interactive speed, without having to physically copy data into other systems or create extracts, cubes, and/or aggregation tables. Dremio’s unique architecture enables faster and more reliable query performance than traditional SQL engines.

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How to Turn Archive Data into Actionable Insights with Cohesity and AWS

A big challenge for enterprises is how to manage the growth of data in a cost-effective manner. CIOs are also looking for ways to get insights out of the data so their organizations can create actionable outcomes. Learn how the CloudArchive Direct feature of Cohesity’s DataPlatform with AWS analytics services to drive insights into customers’ NAS data. Cohesity is redefining data management to lower TCO while simplifying the way businesses manage and protect their data.

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Cognizant-AWS-Partners

Change Data Capture from On-Premises SQL Server to Amazon Redshift Target

Change Data Capture (CDC) is the technique of systematically tracking incremental change in data at the source, and subsequently applying these changes at the target to maintain synchronization. You can implement CDC in diverse scenarios using a variety of tools and technologies. Here, Cognizant uses a hypothetical retailer with a customer loyalty program to demonstrate how CDC can synchronize incremental changes in customer activity with the main body of data already stored about a customer.

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Teradata-AWS-Partners

How to Use AWS Glue to Prepare and Load Amazon S3 Data for Analysis by Teradata Vantage

Customers want to use Teradata Vantage to analyze the data they have stored in Amazon S3, but the AWS service that prepares and loads data stored in S3 for analytics, AWS Glue, does not natively support Teradata Vantage. To use AWS Glue to prep and load data for analysis by Teradata Vantage, you need to rely on AWS Glue custom database connectors. Follow step-by-step instructions and learn how to set up Vantage and AWS Glue to perform Teradata-level analytics on the data you have stored in Amazon S3.

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Clumio-AWS-Partners

Protecting Your Amazon EBS Volumes at Scale with Clumio

Many AWS customers who use Amazon EBS to store persistent data need to back up that data, sometimes for long periods of time. Clumio’s SaaS solution protects Amazon EBS volumes from multiple AWS accounts though a single policy via tagging. Amazon EBS backups by Clumio are securely stored outside of your AWS account in the Clumio service built on AWS, which is protected by end-to-end encryption and stored in an immutable format.

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CloudZero_AWS-Partners

Improving Dataset Query Time and Maintaining Flexibility with Amazon Athena and Amazon Redshift

Analyzing large datasets can be challenging, especially if you aren’t thinking about certain characteristics of the data and what you’re ultimately looking to achieve. There are a number of factors organizations need to consider in order to build systems that are flexible, affordable, and fast. Here, experts from CloudZero walk through how to use AWS services to analyze customer billing data and provide value to end users.

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Zaloni-AWS-Partners

Turning Data into a Key Enterprise Asset with a Governed Data Lake on AWS

Data and analytics success relies on providing analysts and data end users with quick, easy access to accurate, quality data. Enterprises need a high performing and cost-efficient data architecture that supports demand for data access, while providing the data governance and management capabilities required by IT. Data management excellence, which is best achieved via a data lake on AWS, captures and makes quality data available to analysts in a fast and cost-effective way.

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MongoDB_AWS Solutions

MongoDB Atlas Data Lake Lets Developers Create Value from Rich Modern Data 

With the proliferation of cost-effective storage options such as Amazon S3, there should be no reason you can’t keep your data forever, except that with this much data it can be difficult to create value in a timely and efficient way. MongoDB’s Atlas Data Lake enables developers to mine their data for insights with more storage options and the speed and agility of the AWS Cloud. It provides a serverless parallelized compute platform that gives you a powerful and flexible way to analyze and explore your data on Amazon S3.

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How to Create a Continually Refreshed Amazon S3 Data Lake in Just One Day

Data management architectures have evolved drastically from the traditional data warehousing model, to today’s more flexible systems that use pay-as-you-go cloud computing models for big data workloads. Learn how AWS services like Amazon EMR can be used with Bryte Systems to deploy an Amazon S3 data lake in one day. We’ll also detail how AWS and the BryteFlow solution can automate modern data architecture to significantly accelerate delivery and business insights at scale.

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