Microsoft Parallel Data Warehouse Reviews

MPP processing gives us the ability to distribute large data sets across nodes.

We delivered a data warehouse for Contactless and Oyster at TFL.

Improve the speed of processing replicated tables.

We have been using this solution for years.

There were stability issues when the product was in beta.

There were scalability issues in that there is a limit to 32 concurrent queries.

Technical support is good.

We switched from the standard SQL server 2014. We use PDW to improve overall ETL and report performance.

The initial setup was complex. It was fairly challenging to migrate from SQL server to PDW.

Make sure your data volumes are very large: At least 60 million rows per table.

Analysing large volumes of data collected from auto ticket barriers at railway stations.

It has allowed fast daily loads and analysis of millions of rows of data, which eventually moved to near real-time.

It handles high volumes of data very well.

It needs more compatibility with common BI tools. 

It does not work well with normal ETL tools. Some functions do not work.

One to three years.

Microsoft SQL Server Parallel Data Warehouse provides significant performance boost from 10-100 X times faster for data loading operation.It minimized the cost of design with lower infrastructure requirements.It is designed to provide optimized performance on latest industry hardware.

It requires significant infrastructure expertise to implement. Possibility of over specified storage or under specified CPU (need proper planning before starting implementation)It requires significant SQL Server expertise. Microsoft SQL Server Parallel Data Warehouse is purposely built to provide high performance data warehousing. By adopting industry standard hardware it avoids vendor lock-in issue. It is best suited for mid-level to large scale organization.

Both hardware and software support is provided by Microsoft.

We primarily use the solution to build up our server analytics.

The data transmissions between the data models is the most valuable feature.

The database is enormous, so much so that we haven't exploited it completely.

I don't have any recommendations for new features at this time.

I've been using the solution for about one year.

The stability of the solution is good. We haven't had any issues with it.

The solution is very scalable.

My understanding is that the team's experience with technical support has been good.

We didn't previously use a different solution. Our customers chose this solution.

The initial setup was straightforward. We had a knowledgeable team working on the implementation. Deployment took about six to eight weeks.

We use the on-premises deployment model.

I'd rate the solution eight out of ten.

• SQL Data Warehouse provides our organization with a way to access all corporate data in a uniform way. • SQL Data Warehouse allows us to manage our database using network or hierarchical database systems rather than solely relying on relational DBMSs. • It supports the bottom-up process of data warehouse creation where several data marts can be joined to form one big warehouse. I found this very handy especially where a few teams are involved.

• Data cleaning involves the use of special software to help the cleaning team uniformly match attributes from the target source data to its destination. • It is expensive. SQL Data Warehouse is not supported by all versions of SQL Server such as the Express version and therefore becomes unavailable to many limiting its acquisition and use. • Uses a different approach to databases than that used in relational DBMS hence posing a challenge to novices.

• It comes as a special tool of cleaning data through the data transformation process where data is extracted from many sources before it is assembled and consolidated to form a single database. This is the main factor that led my company to choose SQL Data Warehouse as the special tool to consolidate relational databases. Close examination was done on SAP Data Warehouse and IBM Data Warehouse but SQL Data Warehouse provided a more extensive way of integrating data. I personally value the role that SQL Data Warehouse has contributed in achieving the goals of business intelligence. Users will to generate timely reports from huge databases as well as database cleaning should embrace this provision.