What is our primary use case?
We primarily use the solution for analytic purposes. It allows us to store data for years and then go back and look up information to learn things like how users function, react, follow trends, etc. It allows us to follow past and recent demands for products as well so that we might be able to find the reasoning behind the action or trend.
What is most valuable?
With this solution, I can better understand buying patterns and user habits. I can tell in real-time a customer's review and purchase based on that. I can tell that from the cloud data of Azure Data Warehouse.
The solution offers a variety of different features.
There are two layers, so data storage and computation are separated.
For the customer, there aren't any storage limitations, so you are able to explore and size of data including megabytes and terabytes. Once you have stored the data you can analyze the data that if you have in order to write some complex queries. After that, the solution makes it possible to visualize that data itself.
The computation makes it so that you can run scenarios without an impact on your storage location.
If you compare the product to other solutions, you'll notice it takes less time for less cost. All other vendors have different architecture so their pricing is a little bit different and they are charging pricing per second. Microsoft charges per unit, or DTU, Data Transfer Unit. It will charge based on how much data you are consuming and how much data you are doing transactions with. It is monthly not daily.
Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task.
The solution is consistently improving a lot of things, including security features. There are eight or nine different security features there. You can even encrypt your data.
What needs improvement?
There are features coming int he next few quarters that will be helpful. Soon, Power BI will be directly integrated into Azure. We need to have some Spark tools also available so we can directly select customers and don't need to install everything.
There will be features added that relate to application development. There's hopefully going to be more flexibility with the XML. Right now, for example, Data Warehouse is not able to give XML files and your file put is not correct. The feature will hopefully allow us to read XML.
The performance needs to improve in future releases.
We're hoping that Microsoft will add integration with the Amazon AWS platform.
For how long have I used the solution?
I've been using the solution for four years.
What do I think about the stability of the solution?
The solution is quite stable. We haven't had any issues with it in terms of experiencing bugs and glitches.
What do I think about the scalability of the solution?
Microsoft has different sizing options that comes at different price points. It's easy to scale up or down. If you find, after a few years, your needs are growing, you can increase your BTU size the maximum may be about 13,000.
With this solution, we can actually automate scalability, which makes it very easy to scale. If you require more data, it will automatically increase your DP size and process the data. We have the flexibility we need so that, whenever a node gets filled, we never have to worry. Another node will pick up and process the data.
With Snowflake, in comparison, if your system is not running, then Snowflake will go into an auto suspend mode. You can sync the time, and, within the 10 minutes, if the system is not running, it will go to an automatic suspended mode. There is no charge in this mode. In that case, we have to manually find what we need to virtualize the function.
Azure has other mechanisms in place. We can write Azure functions and we can schedule the Azure functions in order to automate them. We can do similar kinds of functionality, however, we have some additional coding we require for Snowflake.
How are customer service and technical support?
We've had no need for support. Everything is automated and pretty much taken care of. We need to configure everything and the Azure portal will get us to the dashboard. In that dashboard, you'll get all of your current information including information on how the system and the cluster is running.
The backend is very nice. There are a lot of additional features that help you manage the product. As users, you will get the visualization dashboard. It is very easy to see, which nodes are running and how much data is processed. We can see everything on the portal, and that makes everything very easy to handle.
Which solution did I use previously and why did I switch?
I've had prior data warehouse experience with traditional systems like the Oracle, Superserver, or Teradata.
Snowflake is the only provider with no cloud platform. You have to buy a platform in order to adopt it. Microsoft Azure, AWS, and Google Cloud all have their own dedicated platform. They have their own dedicated data centers.
How was the initial setup?
The initial setup is not difficult. If you have access to the subscription you can start using Azure Data Warehouse and being to create the services. There are security features also. You can give someone full access, and you can set access for others too. Developers will need access so that they can develop it out. It's a pretty straightforward process.
What's my experience with pricing, setup cost, and licensing?
In comparison, I find that AWS is much more costly.
What other advice do I have?
We're a Microsoft partner.
I have experience with the Microsoft Cloud Data Warehouse specifically within the Unix cloud environment.
We're using the latest version of the solution.
It's important for organizations considering the solution to consider their business requirements and expectations. They need to be clear about what type of cloud solution they are looking for. We help our clients do this and interview them to find out what their needs are so that the best platform can be chosen for them. It may be Azure. It may be Snowflake. It depends on the company's needs.
At the end of the day, the customer will always want the best possible pricing. They'll typically ask how they can save money but have high throughput or more input with less price. If that's the case, Microsoft may be the perfect solution.
I'd rate the solution eight out of ten.
Which deployment model are you using for this solution?