Alibaba Cloud MaxCompute vs. AWS Redshift vs. Azure SQL Data Warehouse

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Data is the currency of the digital world. How your organization stores, organizes, analyzes, and uses the data within its confines will largely determine how successful it is. Enterprises deal with large quantities of data, typically at petabyte scale, and they look to glean maximum value from all this data.

Cloud computing has been a game changer in this respect. What would be cost-prohibitive with traditional servers is now much more accessible with the economic and powerful solutions offered by cloud computing vendors.

Case in point: Data warehouse solutions hosted completely in the cloud. Thanks to cloud-based data lakes, what would have been impossible a few years ago is now made possible by the plummeting costs of data storage disks, and more powerful compute instances. This post explains how to use data warehouses in the cloud, and compares popular options on major public cloud platforms.

Data Warehouse Basics

The first thing to know about a data warehouse is that it is architected differently from small-scale database infrastructure. Rather than having databases that are restricted to hardware servers, a data warehouse is made of multiple servers that work together as a single unit.

Alibaba Cloud MaxCompute

MaxCompute makes data migration simple with a variety of options. You can use Alibaba Cloud’s own tools like the MaxCompute client, or DataWorks, or even popular external tools like Flume, Logstash, or Fluentd. The uploaded data is stored in an SQL database, and can easily be scaled up to petabytes in size.

The most recent version of MaxCompute supports SQL 2.0, and interestingly allows for querying of unstructured data like images and video content. Despite the large quantities of data, and some of it being unstructured, MaxCompute is especially well-suited for real-time analysis. And the best part is that it is extremely easy to use and maintain. MaxCompute handles the difficulty of managing a distributed data store by having unique processes for clustering, indexing, and join optimization which all help with better data storage and retrieval at large scale.

With its recent US launch, MaxCompute is ready to change the way Big Data is processed across the world. With aggressive pricing, it is ready to take on similar services from the two other big cloud vendors — AWS and Azure.

AWS Redshift

A unique feature of the service is Redshift Spectrum, which lets you query data that’s already in AWS S3. This means you don’t have to load your data into Redshift or transform your data. Instead, you can get to querying the data directly. However, if you’d rather have your data in Redshift and you have a lot of it, AWS Glue is an ETL service that makes data loading easy.

AWS recently announced new DC2 nodes which replace DC1 nodes at the same cost. They’re based on Intel’s Broadwell chips and offer twice the performance of the previous DC1 nodes and 30% better storage utilization.

With a variety of options for usage, AWS Redshift is an attractive option for data warehousing in the cloud.

Azure SQL Data Warehouse

Azure has a tool called PolyBase, which is used to query external data without requiring the user to know Hadoop. PolyBase lets you import and export data to and from Hadoop, Azure Blob Storage, or Azure Data Lake Store, or query the data without moving it in and out of SQL Data Warehouse. SQL Data Warehouse is also well integrated with PowerShell, which lets you use scripting to automate common tasks.



Twain Taylor

Twain began his career at Google, where, among other things, he was involved in technical support for the AdWords team. His work involved reviewing stack traces, and resolving issues affecting both customers and the Support team, and handling escalations. Later, he built branded social media applications, and automation scripts to help startups better manage their marketing operations. Today, as a technology journalist he helps IT magazines, and startups change the way teams build and ship applications


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