AWS Partner Network (APN) Blog

Category: Database

How to Enable Mainframe Data Analytics on AWS Using Model9

Mainframe proprietary storage solutions such as VTLs hold valuable data locked in a platform with complex tools. This can lead to higher compute and storage costs, and make it harder to retain existing employees or train new ones. When mainframe data is stored in a cloud storage service, however, it can be accessed by a rich ecosystem of applications and analytics tools. Model9 enables mainframe customers to backup and archive directly to AWS.

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VMware Cloud on AWS_blue

How to Migrate Oracle Workloads to VMware Cloud on AWS

Some Oracle workloads, such as Oracle Real Application Cluster (RAC) or WebLogic application clusters, have specific networking and storage requirements, which can be met with VMware Cloud on AWS. This post details the various considerations and migration options users have for Oracle workloads. Specifically, we examine in-depth how to migrate an Oracle database from an on-premises environment to AWS using AWS Database Migration Service (AWS DMS).

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TDS_AWS Solutions

Creating a Migration Factory Using TransitionManager and CloudEndure Migration

As AWS adoption continues to grow, the need for highly reliable workload migrations at an accelerated pace is paramount. This is particularly true for enterprises turning to AWS to host mission-critical and legacy applications. Organizations need a solution that expedites the migration process, without introducing further risk. TDS TransitionManager with CloudEndure Migration is an AWS solution that accelerates cloud migration projects while reducing risk through automated processes.

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Datacoral_AWS Solutions

Building Serverless Data Pipelines on Amazon Redshift By Writing SQL with Datacoral

Amazon Redshift is a powerful yet affordable data warehouse, and while getting data out of Redshift is easy, getting data into and around Redshift can pose problems as the warehouse grows. Datacoral is a serverless data platform that manages metadata changes, data transformations, and orchestrating pipelines for data consumers. In this post, learn how to write Redshift SQL to represent data flow, and how serverless data pipelines get automatically generated for that data flow.

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Heimdall Data_AWS Solutions

Using the Heimdall Proxy to Split Reads and Writes for Amazon Aurora and Amazon RDS

Horizontally scaling a SQL database involves separating the write-master from read-only servers. This allows the write server to perform dedicated write operations rather than processing redundant read queries. However, writing to one node and reading from another can result in inconsistent data due to synchronization delays. Heimdall Data offers a database proxy to help developers and architects achieve optimal scale from their Amazon RDS and Amazon Aurora environment without any application changes.

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Pivotal_AWS Solutions

Pivotal Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale

Are you thinking of deploying Pivotal Greenplum on the AWS Cloud? Many customers also want to shift the responsibility for infrastructure to AWS, considering the alternatives. With Pivotal Greenplum on AWS, deployments are completely automated and completes in less than an hour. Pivotal Greenplum is a commercial fully-featured MPP data warehouse platform powered by the open source Greenplum Database. It provides powerful and rapid analytics on petabyte scale data volumes.

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SnapLogic_AWS Solutions

Migrating Data Warehouse Workloads from On-Premises Databases to Amazon Redshift with SnapLogic

Amazon Redshift is a fast, scalable, easy-to-use data warehouse solution built on massively parallel processing (MPP) architecture and columnar storage. SnapLogic is an easy-to-learn data integration tool that allows business analysts and integration specialists to accomplish data ingestion from various sources into Redshift. The SnapLogic Redshift Bulk Load Snap (pre-built connector) is part of the SnapLogic Intelligent Integration Platform and enables loading large volumes of data rapidly into Redshift all at once.

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Cognizant_AWS Solutions

Accelerating Data Warehouse Migration to Amazon Redshift Using Cognizant Intelligent Data Works

Many organizations are looking to migrate existing, on-premises enterprise data warehouse systems to cloud-based data warehouse systems such as Amazon Redshift. Here, we discuss how Cognizant’s Intelligent Migration Workbench (IMW) can be used to accelerate the data warehouse migrations while converting Oracle PL/SQL and Tetradata BTEQ scripts. IMW makes it easy to move mission critical proprietary code to AWS, giving customers competitive edge through faster time to market.

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Heimdall Data_AWS Solutions

Improving Application Performance with No Code Changes Using Heimdall’s Database Proxy for Amazon Redshift

Rewriting an application code for performance optimization generally requires a significant amount of effort. Also, IT and development groups using third-party applications like Tableau may not have access to the application code. Heimdall’s database proxy solution offers a flexible and cost-effective alternative to rewriting your application for performance and scale. Heimdall transparently provides SQL control and visibility to the application owner without (re)writing a single line of code.

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AWS Migration

Moving Legacy Oracle Workloads to the AWS Cloud Securely – Yes, You Can! 

AWS Premier Partner Apps Associates, an industry leader for migrating and managing Oracle workloads to the cloud, recently conducted an independent survey of more than 300 Oracle application customers to uncover what’s holding IT decision makers (ITDMs) back from moving their Oracle apps to the cloud. The study uncovered several myths that many ITDMs still believe to be true, although many of these myths have since been debunked—not by declaration but by repeatable, proven success.

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