It's great for streaming and makes everything easy to handle. The streaming from the IoT hub and the messaging are aspects I like a lot.

It is easy to set up.

The solution is stable and reliable. 

It's a product that can scale. 

It is quite simple and straightforward. The product is very user-friendly.

We like that it's using the Azure platform. We can use the old Azure functionality also. We prefer to use the Azure environment. It's something the client uses. 

The analytics and reporting features are okay.

It's scalable as a cloud product.

The solution is stable. 

We use Azure Stream Analytics for simulation and internal activities.

The solution's most valuable feature is the machine learning functionality. It provides the capability to streamline multiple output components.

I appreciate this solution because it leverages open-source technologies. It allows us to utilize the latest streaming solutions and it's easy to develop. 

It also provides quick access to data and allows us to see the results efficiently. Additionally, it offers a graphical view, which helps us understand the data and its transformation. I find this feature quite advanced, and I really like it.

The way it organizes data into tables and dashboards is very helpful, along with its data visualization capabilities.

I basically use two features that are useful. One is Azure Event Hubs, and that is used in conjunction with Azure Streaming Analytics. One is the broker and one is the processing engine. With the processing engine, the SQL way of dealing with things, with streams, is what I like, compared to other solutions, which are more like Scala or Spark-based, where you need to know the language. This was comparatively easy to use with its ability to write SQL on streams.

Technical support is pretty helpful. 

It's my understanding that the setup is pretty straightforward.

I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect. The stream analytics are good and it is a dependable platform.

The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics.

I like the way the UI looks, and the real-time analytics service is aligned to this. That can be helpful if I have to use this on a production service. So this particular Azure Stream Analytics absolutely fits into that. Also, using it requires very few clicks. The UI is set up so that I don't need to spend much time on this. The way that Stream Analytics manages workloads is also good.

We find the query editor feature of this solution extremely valuable for our business.

Also, the multiple window types that are available in this solution, are extremely helpful.

The most valuable features are the IoT hub and the Blob storage. All of the logs and other data that we are getting can be stored in Blobs.

The interface is user-friendly.

The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex.

Our biggest pain point is our housekeeping. We have lot of systems, we must do a lot of configurations and, because of the number of systems is not a simple part of the job, we may forget something. This solution is something which reminds us of what should we do, what stuff is most critical, what we should work on.

The life cycle, report management and crash management features are great. 

The solution's most valuable feature is its ability to create a query using SQ.

Azure Stream Analytics is more user-friendly than AWS. With AWS, there are many components to manage, requiring strong technical skills for cloud usage. Suppose you have explicit domain knowledge and understand your use case. In that case, you should be able to use the product effectively. It's the real-time data streaming feature. You configure it, and it processes coming data. There are some use cases where you want to perform calculations in real time, like edge computing or when you need to make decisions based on the incoming real-time data.

Real-time analytics is the most valuable feature of this solution. I can send the collected data to Power BI in real time.

When it comes to doing partitioning for the data, if you are working with both ModiB and MongoDB, it's very powerful in Microsoft Azure - the clustering platform. If it's Spark Apache, Spark will be very powerful due to the fact that you have the option to have the Delta factory, which makes all that things available within the platform. 

It allows you to take a proactive decision for any abnormal functionality. For IoT, it will give you the facility to make quick decisions on any kind of metrics or output, et cetera.

The solution has a lot of functionality that can be pushed out to companies. There's a lot of analytics to take advantage of. What they have available on the market now is more than enough for companies to work with.

You can install the solution quite quickly and start using it right away.

I like the IoT part. We have mostly used Azure Stream Analytics services for it. This is the most valuable part because this is using the streaming service. It's valuable because there's no other way for us to handle it. 

It has the support of Azure storage, long storage, and access data. It has support from the SQL server. Azure also supports added access to data because we need the data from static data and dynamic data to represent them, and that's not going to change very frequently.

When we are getting the warehouse's location through this stream analytics, we have to merge some information from our static database, and finally, we have to show it all within a dashboard or something on the map.

Without the streaming analytics part, I don't think it's possible to handle it. We can use some other messaging system, but we might have some scaling issues and among others too. I know that Stream Analytics is fantastic in that we don't have to worry about any other activities. We can further scale it too. We can go for the upgraded service if needed, based on our traffic and the number of data we have been receiving.

Natively, I found it beneficial, and the integration was smooth. We're already using some other Microsoft technology packs, so it's easy to integrate them all.

As the Stream input and output enables very smooth integration with other cloud services, for example, Azure Cloud Concepts, or Cosmos DB, with minimum coding, and with the minimum level of queries, we can directly output all these outputs and push the normal data for historical data storage.

The value of this solution is the deep integration it provides with other Azure resources which we use a lot. Our whole infrastructure is pretty much based on Azure so ease of integration is a valuable feature. Secondly, the simplicity of the solution is great. You don't need to set up much, you just make a selection, select a destination, and you're off.