Microsoft Azure Synapse Analytics Reviews

Our general use of this solution has to do with the needs of one of our clients. They had an SQL server and they were migrating from an on-premises SQL Server to Azure SQL server on the cloud. We use this solution because it fits their budget and they have some clients in other countries they want to give access to the product through Power BI.

What I like the most would be MPP (Massively Parallel Processing) architecture. Because we had to migrate a lot of data and it helps us a lot to make things faster.

As far as improvements to the product, I think the Data Factory integration should be enhanced to be properly implemented because right now it is still lagging behind other vendors like Informatica. We ended up having to use Data Factory because we don't have any expertise in Informatica. But I want to see Data Factory get better overall.

An enhancement I would like to see is in data loading for Data Factory. Right now we are seeing a little bit of a performance lapse in the cloud server. Specifically, this happens between Azure and our clients maybe because we are connecting to SQL Server Management Studio. There is a slight but noticeable delay. I do not know if it has to do with Azure and whether it is their problem or our problem.

I can't complain much about Data Factory, but because I used to use SSIS (SQL Server Integration Services) which was the prior on-prem version, I know what capabilities it is missing in comparison. They changed it over to Data Factory, but by comparison, Data Factory has a long way to go to reach the level of SSIS as a product.

Right now is still early in our implementation so I can't really say that I am sure it will remain stable in production under larger loads. But so far it is good and we are happy with the solution and its stability.

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.

I have not had direct contact with technical support. Someone else handles that. But I have not heard any complaints.

The initial set up was not very complex. It was easy to install this product.

We had a partnership with another team and together we did the installation. They helped us to figure out some architectural decisions which they were very helpful with.

My advice to other people considering this solution is that this is a great product. But there is one problem and that is the rate that Microsoft is changing its software implementations. The rapid changes could make it hard to keep up with upgrades. Some of the features get enabled and disabled very quickly. So we are waiting now until everything settles down because cloud technology is still evolving. We understand that. But, on the other hand, as they make so many changes to keep up with the technology, it remains hard to predict what the future of the product is. I might say to anyone that they wait for some time in 2020 and then start using the product.

On a scale from one to ten where one is the worst and ten is the best, I would rate the product as somewhere between a seven or an eight. If I have to choose seven or eight, I would pick seven-out-of-10.

I use this solution for client service forecasting. I work with medium-sized businesses, and I work through a virtual machine.

Synapse Analytics gives you information and reports in real-time.

The platform is not flexible, and the graphical user interface needs to be improved because the interface makes it hard for the end user to use it.

Also, artificial intelligence could be used to improve analytics.

I have used the solution for over a year.

The solution gets support, which helps its stability.

Microsoft's technical support is good when I compare it with other platforms like Oracle. You can also fix many problems yourself because Microsoft has an active community.

The initial setup is easy if you have information about analytics visualization and data warehousing. It's easy enough to install and configure the blade. It takes one day to deploy the solution.

The solution is expensive at the enterprise level. The license is monthly.

Microsoft is a good platform because it's compatible with data warehouse, power analytics, and visualization, and you now have excellent machine learning and AI tools like GPT-4. The platform is also very stable, and support can be migrated for software.

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

I am the Associate Director of a company that is a partner of Synapse.

The solution offers strong scalability opportunities.

I would like to see more ready-to-use products from Synapse. Right now, everything seems a bit futuristic without much modern use.

The solution is scalable.

Price is dependent of the use case of the customer. Customers are not likely to only use this as an individual platform/database, they are likely to bundle it with the Azure stack.

Snowflake is a solution that is much more ahead of the game. There are many gaps in Synapse that Snowflake has fulfilled (i.e. usage, and storage).

Be sure to be clear about the ideal pipeline for Synapse, differentiate your needs, and validate based on use-case.

I would rate this solution a six out of ten overall.

Our general use case is for government purposes, and therefore, I really can't get into too much detail about it.

The solution is great at saving time. Overall, we spend far less time putting together static reports than we used to.

We're able to generate some dynamic reports. I find that very valuable to be able to see our data in such unique ways.

The pricing is pretty good.

The product is very user friendly.

After only using the solution for three months, we haven't yet really gotten into every corner of its capabilities. It's hard to say what might be missing in terms of features.

It would be ideal if the solution could be better used intuitively by the staff without having a great deal of training. An organization should be able to adopt and operationalize it throughout their company with minimal training.

I've been using the solution for three months at this point. It hasn't been too long.

The solution is quite reliable. We haven't experienced any problems with crashing or freezing and haven't really had experience with bugs or glitches. It's stable.

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.

Technical support is okay. I'd rate them seven out of ten. We're satisfied with the level of support we are given.

We were searching for a solution. When we found it, we found something we could use, and then we just stuck with that. We didn't have a previous solution. We had nothing before.

The initial setup is not complex at all. It's pretty straightforward. I'm not that technical, and I was able to handle it.

We've found the pricing to be fair. It's not too expensive.

I'd recommend the solution to other organizations. If they have time, I would suggest a company spends more effort looking at some different offerings. That said, generally, if you don't have a whole lot of money to do something, it's a decent option.

We haven't used the solution for too long, however, it's offered us everything we need in terms of features and capabilities. On a scale from one to ten, I'd rate it at an eight.

We are developing our SQL Data Warehouse locally, using SQL Server 2016 on our private cloud, and we will be migrating it to Azure once it is ready.

The company for which I am working deals with products in the leisure industry, such as museums and swimming pools. They use the data warehouse solution for big data reporting. Currently, we are developing a multi-platform data warehouse that can support the reporting requirements for all of the customers. Whatever analytics they want to perform will be done with the data warehouse, and not the SQL database application.

My role is to design the data warehouse, and once that is complete, we need to build the data pipelines so that the data can be moved from the application databases into the warehouse. Then we will design the OLAP servers and OLAP cubes, vertically, to give us a presentation layer on top of the data warehouse. This layer is what the customers will be using.

The most valuable feature is the incremental load because we do not need to refresh the entire data on a daily basis. We have a nightly load where all of the data is updated, and it is a very good feature.

The transaction log shipping gives us the ability to replicate the database onto different servers for backup and synchronization.

The major concern is that I have a hard time with having to version control the data warehouse all the time. As it is now, I have to open all of the ports and push everything onto the server. I would like to see version control implemented into the data warehouse. This would make the tool perfect. 

I have been using this Microsoft Azure SQL Data Warehouse for about two and a half years.

The version that we have been using, 2016, is stable. We have not used the 2019 version in production yet, but there is a team that is evaluating that version right now. I'm not sure of the reason for it not being in production, whether it is related to stability or not.

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.

We don't have too many technical issues, so overall, I think that it's good enough.

I began with Microsoft SQL Server and have been on the Microsoft platform ever since.

The initial setup is pretty straightforward. It has been a long time since we first implemented this solution, but since that point, we have created a custom handbook that we can follow in order to set it up.

There are certain design concepts that can be used to design a data warehouse. My advice to anybody who is implementing this solution is to first study the user's needs, and then go with that approach. The design will be specific to the needs.

I would rate this solution an eight out of ten.

The healthcare sector is looking for how to accomplish certain processes because currently a lot of it is pure logistics. The goal is to announce and to make processes more transparent and see if they can be made more efficient. This is where business analytics comes in. The organization is using different kinds of information sources, such as electronic client dossiers or HR systems. They will see what kind of knowledge is required, how the patient or the clients are experiencing what quality of health, and create dashboards to see how the organization is doing. This will show which areas they can improve and which areas are already more efficient to make them more visible. This should allow a better understanding from the management, organization, and healthcare professional.

The features most valuable are the simplicity, how easy it is to create a dashboard from different information systems. We are trying to get these organizations to work with the architecture. This should allow these organizations if there is a new product or a new piece of software that is introduced to be able to handle operations themselves. For example, being able to attach the new product to a Power Bl, create a connector, or create interactive information exchange between these two or more different information systems. Standardization and simplicity, are key features.

The solution can integrate well if there is a connector. It will integrate perfectly with the Office 365 suite and Workspace 365.

Indicating what areas need improvement in this solution is a difficult question because the organizations that I am working for are really new in this area. However, an even better more simple interface, or perhaps an extension of a connector app store solution, would be helpful. For example, if your organization, has an electronic client dossier and you want to connect that information system in real-time towards Power BI, you just go to the app store and see if there is an ONS connector, introduce it, set it up, and go from there.

In an upcoming release, it would be beneficial to have the ability to have dashboards on mobile devices to receive a better experience for the user.

I have been using the solution for approximately five years.

This solution is reliable. You have to be aware that you are solely depending on an internet connection. The stability is more about the resilience and reliability of the stability of the network rather than the solution itself.

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.

If I ever have to do call Microsoft support, they are really supportive. For instance, on the Office 365 suite, I had an issue and I received a call back the next day by somebody in the United States. They walked me through the issue and they resolved it within a few hours. They have service-level agreements to attend to and there is good monitoring to see what the status is, the support was really good.

In the initial setup, to make it really easy I have, for instance, just a plain Excel sheet retrieving information in and one information system which brings in live data giving you a good starting point. It is not a really hard setup, to do it is quite straightforward. In the Netherlands, there are some major players concerning electronic client dossiers and electronic patient dossiers. Once you go through the complexity once you can then re-use it for a different customer.

The deployment just takes approximately two hours. It is the testing and the acceptance, and what to get out of the product, that is going to take a longer period of time. This could take up to a couple of weeks to a couple of months.

The type of license depends on what you want. This is a perpetual and monthly license, similar to Office 365.

My company pays for the license and  I am not sure about the price. Sometimes my company wants to have a micro business case study to see if it is an actual benefit for us to purchase. It is a strategic solution and we have to make sure that the organization understands this is going to save them money in the long run.

My advice to those wanting to implement this solution would be to "Think big and act small." See what is up ahead. One of the organizations that I am working for, the big picture is population health management. We are not going to start with that, we are going to start to improve one small process, which is a cumbersome process that is been difficult for many years. That is the process that we are going to make transparent towards the organization, to see where the bottlenecks could be or are, and improve that process. 

We want the user experience to improve and that the amount of time you can save is monitored, which can be used for other care processes. Start with a cumbersome problem, resolve them first. You can actually tell within the organization, if the solution is already working, not on the larger scale, but on the small scale. Once you start seeing these results move on to the next problem.

The solution is secure. However, the organization has to be aware that if you use the security by default, the security is there. It has security by design. It is not the optimal security, I would always recommend that organizations use multi-factor authentication for an additional security layer. Additionally, if possible, have a next-generation firewall within their network in use or, if not, start implementing that if they are planning to move forward into an outsource Azure platform-based eco landscape.

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

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.

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.

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.

I've been using the solution for four years.

The solution is quite stable. We haven't had any issues with it in terms of experiencing bugs and glitches.

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. 

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.

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.

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.

In comparison, I find that AWS is much more costly.

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.

We use it for reporting purposes and for building data warehouses, pipelines, and data lakes for IoT projects.

I like how Microsoft Azure Synapse Analytics integrates with other Microsoft solutions. 

Real-time integration is hard to do in Microsoft Azure Synapse Analytics.

I've been using Microsoft Azure Synapse Analytics for two years.

I would rate the solution's stability at nine out of ten.

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 documentation is good, but if you cannot find the right documentation and the right steps, then the initial setup can be hard. I would rate the initial deployment at seven out of ten.

This solution is deployed on the cloud, and it took half a day to deploy it. I configured the data lake storage, created the workspace, and added users and user rights. Building pipelines is a straightforward process.

I think Microsoft Azure Synapse Analytics is priced well, and I would rate the price at eight out of ten.

On a scale from one to ten, I would rate Microsoft Azure Synapse Analytics at seven. Other solutions have more user-friendly and intuitive interfaces.