Scalability is built in. You don't need to do anything. If you're working with a terabyte of data on one day, you can go up to a petabyte the next day. There's no need to worry about scalability in terms of performance.

The solution is scalable.

The product can scale. 

For one of my clients, it was used as an Enterprise Data Warehouse, so it has got all kinds of insurance functions, and users. It has got an underwriting team, it has got the actual team, it has got a claims operations team, et cetera. All the enterprise Data Warehouse users start consuming data while using the visualization tools like Boll-BI, and then MicroStrategy, et cetera.

It is pretty much infinitely scalable if you got the money to pay for it.

Currently, we probably have 600 or 700 users in the county. They are mostly data analysts and data scientists. As far as developers go, we probably have 15 developers working with it right now.

Microsoft Azure Synapse Analytics is created out-of-the-box to be scalable. That was always the struggle of Analytics and BI Teams you had to spend $2 million to receive the server with RAM and disk space needed to use this type of solution. Microsoft Azure Synapse Analytics will scale automatically behind the scenes. Which is one of its main powerful features.

We have many people using the solution. The data engineer, who is moving data around and brings data in. The data scientist and the IoT developer. There are different areas in Microsoft Azure Synapse Analytics for each role.

We manage four to five Microsoft Azure Synapse Analytics customers in our environment. It is a scalable software.

Azure products are highly scalable, so I would rate it nine out of ten. 

I will rate the scalability an eight out of ten. It depends on how much you scale it, but it's been proven to be quite scalable for what I'm working with.

Around eight end users are using this solution. The usage frequency depends on the job. Sometimes, it could be almost every day, depending on if we're receiving a lot of information. And at some point, it's quite slow, so we have to be on it almost every few days to check and update.

So, in the future, we may use it more than we are using it now.

I work for Accenture, so there are hundreds and thousands of customers on Microsoft.

The solution scales very well. You can scale up or down as required. It's very easy.

It is a scalable solution.  

Microsoft Azure Synapse Analytics is able to scale to the needs of our requirements.

Azure cloud is very scalable and allows this product to scale as well. We can scale horizontally and vertically.

I rate Synapse 10 out of 10 for scalability. Scaling up Synapse is quick and easy. That's one thing I appreciate the most about it. You can scale with a click 

The solution is scalable.

We use the solution intermittently, approximately 50 percent of the time.

We have approximately 1,500 users using the solution.

I rate the scalability of Microsoft Azure Synapse Analytics a ten out of ten.

The solution is very scalable. We are a medium-sized enterprise, and there are almost 4000 end-users.

The solution is scalable. Generally, the development team of around 20 people uses Azure Synapse Analytics directly. Otherwise, a Power BI dashboard accesses the Azure Synapse Analytics database, and the end user uses the Power BI reports, not being directly exposed to Azure Synapse Analytics. Only the development and software development teams use Azure Synapse Analytics.

The solution is a web data warehousing and analytical platform built for enterprise environments, so it is definitely scalable. 

I haven't seen any issues with scalability. 

The solution is scalable.

We have about 20 people using the solution in our company.

The solution is scalable. We currently have fifty to sixty people working within it and, now that we are using Serverless more often, we are planning to have more people working with it.

As Microsoft Azure Synapse Analytics is on the cloud, it's scalable, and you won't have that many issues with scalability. If a solution is cloud-based, you won't have to worry about whether it's scalable or whether it supports other features, because you'd have all features in the cloud itself. You can scale up or scale down Microsoft Azure Synapse Analytics based on your requirement, so it all depends on what exactly you want. In the cloud, you won't have to schedule, wait, think, or plan. You can scale up or scale down automatically anytime.

The solution is scalable to a customer's needs. A few customers have written scripts to scale how they want, but most customers use the out-of-the-box database.  

I rate the scalability of Microsoft Azure Synapse Analytics an eight out of ten.

Microsoft Azure Synapse Analytics is scalable.

The Azure Synapse service is highly scalable. 

It is simple to scale the service. I'd rate it at ten out of ten for scalability. We had 45 engineers who used the solution.

The scalability of Microsoft Azure Synapse Analytics is very good.

We have hundreds of people using this solution.

It's scalable. I'd rate it an eight out of ten in terms of scalability. Our clients are enterprises. 

We can scale the product up and down according to our needs.

We have around 100 people using the solution right now. 

My customer uses it on a daily basis.

The solution is scalable.

The solution can scale, however, it is expensive to do so. If a company wants to expand, it will have to pay. Therefore, they should be prepared for that.

Currently, we have about 200 people using the solution.

The scalability of Microsoft Azure Synapse Analytics is good.

The scalability of Microsoft Azure Synapse Analytics is very good.

We have approximately 40 people using the solution. We have plans to increase our usage in the future.

I'm very impressed by the scalability of Synapse Analytics, even though we don't use it for huge amounts of data most of the time. Combined with the availability of machine learning and other features in the cloud, it has a lot of potential, especially in the area of finance.

Azure Synapse is serverless architecture, so you can scale as and when required. It makes no difference if there are 100 users or 1,000 users. We have around 50,000 end users.

Synapse Analytics is definitely scalable.

The solution is scalable. I have changed the interface and most of the operations can be done from the interface by clicking a few buttons, it is quick and easy.

At the moment we only have approximately four people using the solution because it is a data warehouse creation in the back end. We have not reached the stage where our staff will use the product but we are building a single customer view using the platform and we will be increase usage in the future.

For the amount of data that we have, Microsoft Azure Synapse Analytics has worked perfectly fine in terms of scalability. Thus, for us the scalability is a ten out of ten.

The solution is highly scalable. For example, if you have 100 DWUs, you can increase up to 20,000 DWUs by letting Microsoft know your requirements. Your needs for DWUs will be satisfied based on how much you are willing to pay.

It's a scalable solution.

Our client's companies vary in size. They are across the board from insurance companies, healthcare, marketing, and manufacturing.

This solution is scalable, although I don't expect that we will expand it beyond the current usage.

We have not tried to expand the solution into a very large extension because it is a rather small organization that I am working for. The Azure platform where Power BI is running on is expandable to whatever you like.

We have many organizations using this solution. The care organization I am working for has three customers using it. I am also working as an associate with another company and they have multiple organizations that are working with these solutions. My estimate would be approximately 15 organizations that are working with this solution.

We have plans to increase usage, but these organizations are all at the starting point. This is a strategic solution to improve their processes and business continuity. It is a conservative environment, every change is really hard. It is really stressful to get changes done and it will take some time. This solution changes the way in which work is done, it will take up to three to four years to be widely adopted.

This solution is quite easy to scale depending on your workload. Overall it is a little bit expensive. You have to know exactly what you are doing as you scale up, otherwise the cost goes up quite quickly.

For its traditional data warehousing, it's scalable.

For Synapse Analytics, I am uncertain about being able to trust it with large volumes, which is what you would expect with Databricks.

There are only three or four people in our organization who do this type of work.

This solution is scalable.

We have a couple of administrations using this solution and the rest are indirectly using third-party tools. They are developers and administrators.

One of the reasons we decided to go with Azure was because we knew we could scale-out. We were happy with this scalability before we committed to the product.

Right now, I know only two of our clients are using the solution. They are actually a government organization. But we know we can scale up when we have to.

On the client's side, there are approximately 100 users of this solution.

While I haven't really tested the scalability, it is my impression that the solution can scale and it shouldn't be an issue for any company to do so.

You can scale it, although you need to put in more effort. We have approximately 800 users.

I think the architectural design is very scalable.

The scalability has been pretty good, in our experience. We have been able to scale it twice to the number of users we needed. We were also able to double the amount of data load. We haven't had issues. If a company needs to expand, it should be able to do so without problems.

Synapse Analytics is deployed in a cloud environment and one of the best advantages of this is that it provides scalability.

Synapse Analytics is a scalable product.

It's a scalable solution and we find it to be easy to scale.

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. 

The scalability is good. I think we are already using a high availability cluster for 2016, so I assume that it will be the same with the 2019 version. We are also using it with our data recovery system, so it is not an issue.

We have approximately twelve to fifteen developers and approx. 900+ customers who will be using the data warehouse. We are acquiring customers on a monthly or quarterly basis, so it is a pretty big user base and we expect that our usage will continue to increase.

It is scalable to a certain limit. It is not as scalable as Snowflake, but it is scalable.

The solution is scalable. It's online. That means you can scale it online and can stop the database to change the scaling of it.

We do plan to increase usage and we may hire a consultant to help with an expansion in a few months. This will likely happen, however, anything can change in terms of the business and the larger industry.

Scalability is good. I foresee scalability in terms of the possibility of using more features and the only difficult thing that I see already is the macros of the Excel spreadsheets. I also know that it has a good opportunity for scalability, in terms of the more complex tasks that can be achieved. 

Currently, we have ten people on the solution.

Scalability is something that is improving.

Scalability is good and we haven't had any issues.

We have approximately 150 users. We are stable at the moment but we will expand our usage as we get more data.

Its scalability is good. The only thing is that when you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

This solution is scalable.

Scalability is one of the main advantages of this solution.

The product is scalable. 

In principle, it's a limitless, serverless solution. As long as your region has resources, you can go on expanding. We have not had any problems with scalability.

Microsoft Azure comes integrated with Databricks as a Machine Learning platform, it's highly scalable.

The solution is scalable. A company shouldn't have issues expanding it out.

In our organizations, we have less than a dozen users, and those are mostly IT and IT management people.

Scalability is the best part of going with a cloud-based solution. I don't have to worry about server space. Azure elasticity allows us to scale as much as we want, and it is pay-as-you-go, so we can scale up as we need to. What we propose to the people who are implementing this solution is to start with the minimum requirements and then scale up based on demand.

We have three to four people using the product.

We are satisfied with the scalability.

A lot of people use the analytics and I would estimate it to be between 50 and 100 users. Most of them are business users, although some are power users who built the system for them.

This scalability of this solution is five out of five. It is easy to scale, although it is a bit pricey compared to the competition, even with the Microsoft discount that we get for being a big enterprise.

We have approximately three hundred users for Azure SQL. With respect to Power BI reporting that can run queries in Azure SQL, I think that there are thousands. We have no plans to expand at this time.

It is a Cloud platform and so it is easy to scale.

We don't scale up because the current level is enough for our customers. Our customers are small and medium companies in Europe.

Scalability is great. It can go from zero to infinity. 

We haven't grown a lot so I am not able to say if the solution is scalable or not.