Microsoft Parallel Data Warehouse Reviews

For the last 10 to 12 years, I've worked as a data engineer on different projects, and in some of them, we have used Microsoft Parallel Data Warehouse. It's something that I've worked on and off for quite some time, but not something that I work with on a daily basis.

The biggest advantage of Microsoft Parallel Data Warehouse is the possibility to stop or pause the service because it can be very expensive, and the ability to pause the service when I don't use it is probably the main feature, along with the possibility to handle huge amounts of data, which is quite an interesting capability of the service.

Microsoft Parallel Data Warehouse can be a cost-saving solution, but in general, it's considered to be an expensive service. If I know how to handle it, it can be cost-saving, especially with the feature I mentioned earlier about pausing the service when I don't use it, which is a significant cost-saving feature. Still, at the end of the day, it remains somewhat expensive, making more sense for very specific use cases where I have to handle huge amounts of data; for medium or small use cases, it doesn't really make much sense.

There could be improvements on the cost side of Microsoft Parallel Data Warehouse because it is still considered to be quite expensive by a lot of users, and many companies are not interested in solutions with parallel data warehousing due to this expense. Addressing the cost would be the number one area for improvement. Additionally, I have not worked recently with it, so I don't know if this feature already exists, but if it doesn't, having an elastic feature that adjusts the service's power dynamically based on the workload would be beneficial instead of fixing the power at a specific level.

For the last 10 to 12 years, I've worked as a data engineer on different projects, and in some of them, we have used Microsoft Parallel Data Warehouse. It's something that I've worked on and off for quite some time, but not something that I work with on a daily basis.

Microsoft Parallel Data Warehouse is a stable solution.

I would rate my experience with technical support around six on a scale of 1 to 10 because I have not had a particular experience with technical support. I don't remember ever creating a ticket for Microsoft regarding a particular technical issue with Microsoft Parallel Data Warehouse, and I don't recall a specific case from other colleagues or coworkers. Generally, Microsoft can be good, but overall, I would rate it around six.

Positive

I remember that my initial setup of the solution was relatively easy, but that also depends on the specific case. In general, using it is not that difficult, so I would say it's relatively straightforward.

On the integration side, Microsoft Parallel Data Warehouse is quite good as far as I stay within the Azure or Microsoft services. The integration is quite good, but I don't have specific experience combining it with other services, so I don't know how easy or difficult it is to integrate otherwise. However, as far as I work with Microsoft services or Azure data services, I would say there is good integration possibility.

I have some experience working with Microsoft Analytics Platform System, Oracle Big Data Appliance, and Microsoft Parallel Data Warehouse.

I rate Microsoft Parallel Data Warehouse a seven out of ten.

These are all very custom development for the customers. I work for my customers as a consultant, so whatever platform the customer has, we provide services on that platform. We are platform agnostic.

My personal preference is Microsoft Parallel Data Warehouse, and I'm doing some consulting work on that, and actually hands-on work also.

I'm very pro Microsoft because I think Microsoft products are highly intuitive and are widely used. The integration capability is good, and it integrates pretty easily with multiple ways of doing something.

Microsoft Parallel Data Warehouse keeps giving updates and new features. In my first consultancy, I transitioned a mortgage company from Oracle OBIEE to Microsoft Parallel Data Warehouse to greatly reduce the mortgage approval time. There's a feature that allows users to set alerts on triggers within reports, enabling timely actions on pending applications and effectively reducing waiting time.

It extracts data from the ERP system, and we are doing extensive data analytics. The system handles target marketing for a company which does 85 to 90% of its business in wholesale. We have a variety of clients from mom-and-pop stores to big box stores, and we have intermediaries. We sell through approximately 13 retail channels including Etsy, our retail website, Faire, Wayfair, and Walmart.

Each channel requires different types of inventory updates and packaging, which is managed automatically. A significant amount of development is done on Microsoft Parallel Data Warehouse where all these processes are automatically fed out and updated. We also conduct inventory analysis and aging analysis. We identify seasonal buyers, track their purchasing habits, and auto-trigger campaigns for them, sometimes offering discounts on various items. We've found that combining top-selling items with non-selling items can lead to increased sales, as people often buy additional items when they find one on sale.

The patch releases are a concern. For a customer with tons of servers, frequent patches lead to required reboots, which interrupts business. It would be better to release patches less frequently, maybe once a month or once every two months.

I have been working with this customer for the last couple of years.

I haven't found any stability issues thus far, rating it at nine out of ten.

As a consultant, we hire additional programmers when we need to scale up certain major projects. We don't keep programmers on our payroll but hire them as needed. For smaller support tasks, I'm very hands-on, so I can take care of day-to-day issues.

That project was completed and I never worked on it after that. Microsoft Parallel Data Warehouse deserves a rating of eight out of ten. It is not as expensive as Oracle, but it is still expensive. This afternoon, I resolved an issue where we needed our database CPUs to increase, and the pricing of this Microsoft Parallel Data Warehouse license increased along with that, which feels unreasonable.

Overall review rating: 8/10

The basic use case for us is virtual machines. In real estate, we use it for our operations. They handle large data sets well, and the performance is good during those times.

I believe the product is pretty fast. When I have used it, it is handy. The integration with other Azure products is good and integrates well. Microsoft Parallel Data Warehouse's security measures help ensure our sensitive data protection during analysis through measures such as encryption. Its scalability is impressive as it scales up and down really well. We go from a couple of users to tons of users all the time, and it scales and handles things really well. One of the major benefits with this product is that it's Microsoft, which is one of the best ones, and it's just plug and play.

The pricing could be better; I think it actually just went up.

I have used Microsoft Parallel Data Warehouse for two years.

No stability issues were experienced.

The scalability is impressive as it scales up and down really well. We go from a couple of users to tons of users all the time, and it scales and handles things really well.

I haven't had to deal with customer service myself, but we have as a team, and they are good. They are responsive and get back to us. On a scale of one to ten, I would rate them probably an eight for the support for our team.

Positive

We have dealt with Citrix and moved away to Microsoft Parallel Data Warehouse.

The initial setup was, as far as I am aware, pretty straightforward for the team that did that.

Microsoft Parallel Data Warehouse

We use some of those types of products. I am familiar with providing a brief review on products. The price, support for the product, and how easy it is to set up have been good so far. We are using other Microsoft tools as we are a Microsoft shop. I dealt with the Remote Desktop Services as well, and it would be the same thing. We use Microsoft Parallel Data Warehouse for that, too. I can answer questions regarding the Remote Desktop Service and its associated features. My overall rating for this review is seven.

Neutral

I use Microsoft Parallel Data Warehouse to construct and manage a data warehouse. I mainly write SQL queries to manage the data.

The interface is very user-friendly. It's great for managing the data warehouse efficiently when well-managed.

When there are many users or many expensive queries, it can be very slow.

I have been using Microsoft Parallel Data Warehouse for three years.

It is very stable based on my experience.

Scalability could be improved. I would rate it seven out of ten.

I did not use any other similar solution before Microsoft Parallel Data Warehouse.

The installation took less than one hour.

We used a third party for the implementation.

I recommend this solution as it is very stable and, when well managed, can be efficient in organizing data.

I'd rate the solution eight out of ten.

We use it to build our data warehouse and databases, and everything in the back end.

It helps streamline our metadata warehousing process. As it is our only type of data warehouse and database, it serves as our source, destination, and staging area.

This product has many features which are useful to our team. It is very strong, scalable, and has tons of features. Since almost everyone in our tech company is used to SQL Server, it is our best choice.

There are many areas for improvement. A major issue is with table statistics. Sometimes the statistics are not refreshed correctly, which causes issues for us. When we update a table, it should trigger a status update, but sometimes it does not. This requires manual intervention.

Our company has been using SQL Server Data Warehouse for over twenty years. Personally, I have been working with the SQL Server for around ten years and with this company for a little more than three years.

If we have a large table, it significantly slows down our reporting process. We have to do some indexing and partitioning to make the table run faster. Scalability is not a major problem right now, but it can be a drawback to our reporting process.

Customer service for this product is rated seven out of ten.

Neutral

We have always used SQL Server Data Warehouse and have not used any other data warehouse solutions.

The initial setup is very straightforward. It only takes one or two days to deploy.

At least one developer and one DBA need to be involved in the implementation, so at least two people are required.

We have seen a one hundred percent return on investment as this product is integral to our back-end operations.

I am not very sure about the pricing or licensing.

I would recommend SQL Server. It is very useful. I'd rate the solution nine out of ten.

Neutral

In my company, we use Microsoft Parallel Data Warehouse in some of our projects, including loading the data of multiple data locations in France to employed data warehouses.

The most valuable feature of the solution is SQL Server commands that we use in our company since it allows us to write stored procedures or different stored procedures, which we can call from Visual Studio where it is stored. SQL is faster compared to SSIS, so we can use stored procedures from there.

In my company, everything is shifted to Azure Cloud instead of SSIS. I am learning more about Azure. I use SSIS when there is a huge amount of data and we have to load the data in chunks, making our processes a little slower. The overall performance could be faster.

I have been using Microsoft Parallel Data Warehouse for around six years now. I use Microsoft Parallel Data Warehouse Version 19, which is the solution's latest version.

It is a stable solution. The only issue with the product is that the process is very slow when we have a huge amount of data.

It is a scalable solution.

In my company, around 16 people can log in to use the product at a time.

The initial setup was fine and straightforward.

The migration process related to Microsoft Parallel Data Warehouse has been going on for a month in my company. We have multiple labs, of which it was possible to load the data in 47 labs. With one lab, it took almost a week to load the data since the data count was in millions, due to which it initially failed multiple times, creating a huge issue for us. It's all done right now, but we have faced issues in the past.

In our company, we created new databases in the new SQL Server. We replicated the databases, and then we got the data from there.

The installation was done with the help of a third party.

Octopus Deploy holds the deployment part of the solution. In our company, we develop solutions, and we can deploy them with Octopus Deploy. In our team, we have eight developers, and we can do the deployment at the same time, but Octopus Deploy does the deployment one by one, in the order starting from the first person who applied for the deployment.

Regarding ETL tools, I have used SSIS and some experience in OBIEE. I have experience with multiple other solutions, including some from Microsoft. I have heard of Informatica, but I am not really sure how good it is overall.

Considering that I have just started using Azure and everything is shifting to the cloud, I will recommend Microsoft Parallel Data Warehouse since it is easy to use and feasible.

Overall, I rate the solution an eight out of ten.

I use it at the office to access data.

The solution's integration is good, and visualization happens in Power BI, making it convenient. Likewise, the solution has free features. It is not that expensive when we try to make it public on our portal.

Some compatibility issues occur during deployment, so we need to build the product from scratch for some features, which should be a real concern for Microsoft. When I read some of the packages from 2012 and needed to transform or upgrade them to 2019, they were not directly upgradeable. You have to make manual changes, and you can only upgrade it.

I've used the solution for five to six years.

The solution is stable for medium to large-sized organizations, though I haven't used it on a large scale, like on petabyte-sized databases. Things are working fine on terabyte-sized databases. ETL can be automated, and job scheduling can be done relatively fast. Even the control dome of servers can be configured. Maintaining the SQL Server database would be easy for a DBA who has used any other databases like Oracle MySQL or PostgreSQL.

It is very easy to scale the solution.

The customer support is good. I was concerned with Office or some other tool; they were approachable. If you have the concern and the license, you can chat with them, and they will help address your concerns.

The initial setup is okay, but that can also be improved. They could integrate the solution into Visual Studio into SQL Server and get things done. Deploying the packages requires going through an interface in SQL Server and then going through Microsoft Visual Studio instead of doing it directly from SQL Server. The deployment does not take that much time, but it will take a little time.

Maintaining the solution is easy. At some point, you could do something, and it could break, but I can find the logs, find the error, work on it, and resolve things.

We are client-based, and 50% of our clients use Azure and SSIS data warehouse, MSBI. Anyone planning to choose Microsoft Parallel Data Warehouse can go for it. I rate the solution an eight out of ten.

Our customers use Microsoft Parallel Data Warehouse to manage large volumes of data and perform complex queries efficiently. Its performance is generally superior compared to other solutions, aiding in the efficient handling of large-scale data analytics projects.

The key features impacting our data management processes are the handling of data limits and its integration with business intelligence tools such as Power BI. Additionally, its pricing and seamless integration with Azure solutions are significant advantages.

The product scalability needs improvement. 

I have been working with Microsoft Parallel Data Warehouse for more than ten years.

The platform has been reliable in handling large volumes of data and complex queries.

The product scalability needs improvement compared to solutions like Snowflake and BigQuery.

I have worked with BA systems and hold some certifications with Snowflake.

The initial setup was straightforward, with integration and data modeling being the more complex aspects.

We implemented the product with the help of our in-house team.

The solution has provided a notable return on investment by managing large data volumes efficiently and integrating seamlessly with our existing tools.

The solution is cost-effective, especially considering its seamless integration with Azure. However, the cost can be a challenge, particularly for customers who prefer on-premises solutions.

We evaluated other options but chose Microsoft Parallel Data Warehouse due to its comprehensive features and integration capabilities.

We integrate SQL Data Warehouse with our infrastructure, leveraging its strong integration with Power BI. The solution's cloud-based nature facilitates easy integration with our system, providing significant advantages over other solutions like Google’s.

I rate it an eight.