Microsoft Data Warehouse Solutions

Microsoft offers the most comprehensive logical data warehouse solution for on-premises and the cloud. In the case of the cloud, we are talking about Microsoft Azure and Office 365 with integration of services like Power BI, PowerApps, Flow, SharePoint and other software-as-a-service productivity applications.

In our experience, SQL Server 2017 Data Warehouse features provide the best performance, security, and high availability compared to other popular databases on the market. Here is how Microsoft promotes their advantage over other platforms:

In addition to using SQL Server 2017, Microsoft offers the Analytics Platform System with appliance offerings from HP, Dell, and QCT for massively paralleled processing power that can scale out to 6 petabytes of data.

Likewise, Microsoft Azure data services featuring Azure Synapse Analytics (previously Azure SQL Data Warehouse) and Azure Data Lake Analytics provides great on-demand scaling with competitive pricing. More importantly, you have excellent integration with other services like the Microsoft AI platform and open source solutions.

Everything you hear from vendors like Microsoft is that their platform provides the freedom of choice. The problem is when you have too many choices!

Here is where the decision-making process becomes interesting.

Virtual machines: Microsoft, AWS, and Google continually improve server technology with more cores and more RAM. For example, you can provision a server with up to 128 cores and 4 TB of RAM that can support 30 TB of data on SSD storage. If you then consider using SQL Server 2017 PolyBase with scale-out groups to connect to one of the supported Hadoop distributions, Azure Blob Store, or Azure Data Lake Store, you can effectively extend your data warehouse limited only by your cloud spending limit.

• Tip: Based on our benchmarking and customer experience, running SQL Server on virtual machine solutions for Azure, AWS, and Google Cloud will give you greater performance per dollar for up to 15 TB data warehouses compared to Azure Synapse Analytics. Of course, you need to manage the server. However, Microsoft Azure provides manageability features like automated patching within a scheduled maintenance window, automated backups to blob storage, Geo Redundant Storage, easily configurable Always On Availability Groups with readable secondaries, Azure Site Recovery, and pre-configured VM templates optimized for data warehouse solutions.

Azure Synapse Analytics: This solution offers a cloud-based massively parallel processing (MPP) data warehouse architecture similar to the Microsoft Analytics Platform System. Due to the MPP architecture, we recommend, based on guidance from Microsoft and our own experience with customers, considering Azure Synapse Analytics for data warehouse sizes 10TB or more. You get essentially unlimited scale with PolyBase capabilities to integrate your cloud-borne dark data with data from your enterprise data warehouse.

• Tip: Don’t consider a proof of concept pilot unless you have at least 10 TB of data from your data warehouse. We’ve had first-hand customer experience migrating small Oracle Data Warehouse solutions to Azure Synapse Analytics under 5 TB, where performance was substantially slower than the original Oracle database system. Once we increased the data over 10 TB, Azure Synapse Analytics performance was significantly faster with a great price per terabyte savings over the Oracle solution.

Oracle and Microsoft prohibit us from publishing benchmark values, but you can contact us directly to learn more about migrating your Oracle Data Warehouse databases to Azure Synapse Analytics.

Azure Data Lake Store: This serverless based solution, along with the U-SQL for querying non-relational data across a variety of data sources, provides a great way to understand your dark data.

• Tip: Consider using just Azure Data Lake Store to analyze your dark data. If you discover data that needs to get incorporated into your Enterprise Data Warehouse, go ahead and update your data model and ETL processes to load the data into either Azure Synapse Analytics or SQL Server running on an Azure VM. You can then incorporate your standard practices of using data cleansing, master data management, and optimizations with Analysis Services for a consistent view of the data for business decision makers.

Here is a great overview provided by Microsoft to better understand the choices available to get the most out Microsoft Data Warehouse solutions.

We have a variety of offers and incentives from Microsoft to help you get started with our team of experts to future-proof your data warehouse and analytics solutions.

We start with assessing your data environment. At the beginning of a project, you discuss existing database deployments and tools with a dedicated ABCloudz project team. This step helps establish the information, resources, and team members needed from your side.

You then make your data infrastructure available to trusted ABCloudz team members. We use this access to identify issues and craft a modernization path that fits within your current environment.

Our proficient solutions architects then design the future-state cloud architecture of your data environment. Our experienced team can provide you with comprehensive technical and financial information about the potential pros and cons of any proposed modernization project.

As a result, we can either provide your team with cloud deployment scripts, recommendations, and suggestions, or go all the way and create the cloud infrastructure using our manpower.

Here is a sample of our featured services related to data warehouse solutions using the Microsoft platform.