Microsoft Azure Synapse Analytics Reviews

What I found most valuable in Microsoft Azure Synapse Analytics is that it's native only for Azure, so you get better performance and there's no issue. To explain further, many different types of data come, in particular, structured and unstructured data. For audit purposes, there's also unstructured data, so the most important aspect is that with Microsoft Azure Synapse Analytics, you have the capability of using both technologies, meaning that you can use or mix structured and unstructured data which is important. This can also be done in Hadoop, and on other platforms, so you have everything in one place. You don't have to worry about how to manage both structured and unstructured data and where to store information. With Microsoft Azure Synapse Analytics, you can take care of everything, particularly in Azure.

The solution also provides you with many features apart from analytics, for example, storage which makes it better.

An area for improvement in Microsoft Azure Synapse Analytics is its user interface. You can use it for analytical purposes, but its platform should be a little bit more user-friendly.

Another small point for improvement in Microsoft Azure Synapse Analytics is its stability. It's good currently, but it could still be improved.

Microsoft is combining different tools and technologies into one solution, so in the future, I'm expecting to see even more improvement in Microsoft Azure Synapse Analytics.

An additional feature I'd like to see in the next version of Microsoft Azure Synapse Analytics is the drag-and-drop feature. If you're doing some integrations where you can write Scala or you have SPARK programming or SQL, or you're combining different programming, the process should be seamless, and you should be able to drag and drop in Microsoft Azure Synapse Analytics. When doing reporting in the solution, you should also be able to drag and drop. There should be connectors available and a drag-and-drop feature available in the user interface of Microsoft Azure Synapse Analytics, so you won't have to worry about how all processes would work together. You need to be able to drag and drop even from the backend, and having this feature will make the solution more user-friendly.

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

In my opinion, Microsoft Azure Synapse Analytics is stable. I would rate its stability seven out of ten.

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.

I'm working on behalf of a vendor for the client, so my team is supporting not just users of Microsoft Azure Synapse Analytics within my company, but several other companies as well. Apart from supporting the infrastructure, data-related services, and other services, my team provides a combined type of effort for clients. My team is a big team with people working together from three different companies providing support for Microsoft Azure Synapse Analytics. My team provides technical support for the solution.

The initial setup for Microsoft Azure Synapse Analytics is straightforward because Azure makes it very easy. Any Azure solution is very user-friendly, but you just have to know how to use the solution, and that's it. Setting up Microsoft Azure Synapse Analytics is not that complex if you're knowledgeable.

I evaluated AWS, and if you compare Microsoft Azure Synapse Analytics with AWS, Azure excels more than AWS.

Amazon or AWS is established, and there's no doubt about it. It's also less costly in comparison with Microsoft Azure Synapse Analytics, but since I worked on both platforms, if you want everything where you have to pay a little bit, and you don't want to pay or invest in some other development areas, and you want certain features to be automatically available for you, apart from a lot of features to be available on any platform you use, then your choice should be Microsoft Azure Synapse Analytics. Amazon is a cloud provider only and relies mostly on open-source, but Azure has support from Microsoft which is an innovative company. Whatever product is offered by Azure, Microsoft support is there, and as a company, Microsoft is always very innovative, so a product such as Microsoft Azure Synapse Analytics is very useful and very user-friendly, which you won't get that much, at least for now, from Amazon. If Amazon wants to be comparable to Azure and have the same capabilities, then it will need to depend on some other companies. Whereas for Microsoft products, for example, GEO, it's native to the Microsoft platform, so it's comfortable to use, even though it's open-source and you're never sure of what type of problems could arise. Microsoft Azure Synapse Analytics, because it's an Azure or Microsoft solution, is more advantageous than AWS.

I'm an architect and I'm using Microsoft Azure Synapse Analytics, and apart from that solution, I'm also using other types such as Big Data, AIML, SPARK, and Scala. I'm also into other languages and reporting services.

I'm using the solution for my clients. Currently, I'm using it for clients, particularly Netherland-based banking institutions that have a cloud setup on Azure, but the deployment is now hybrid because of an ongoing migration. It's not completely migrated yet, so there's still something left in the data center. The clients have an ongoing migration from Hadoop and SD inSITE as well, which would be moved completely to Azure Cloud, so as of now, the deployment of Microsoft Azure Synapse Analytics is still hybrid.

My rating for Microsoft Azure Synapse Analytics is seven out of ten as it combines many different features that you can use, so it's a good solution, and in the future, I'm expecting it to be better and better.

Several teams use Microsoft Azure Synapse Analytics, but then in my team, around twenty-five people use it, but that's not the complete number of users. Many people use the solution, with different features being used.

I don't see a product comparable to Microsoft Azure Synapse Analytics that's available on the cloud. Currently, there's no comparison, so you can't say whether it's good or bad, though room for improvement in any product will always be there. Based on all the features of Microsoft Azure Synapse Analytics, my rating for it is seven out of ten, at the moment, there's no competition for the solution because I've not come across any other tool that's comparable to Microsoft Azure Synapse Analytics.

We primarily use the solution for our cloud data warehouse. 

The usability has been excellent. 

It offers good integration. 

The product works well with other Azure products.

The initial setup is very convenient.

It is scalable.

We have found the solution to be stable. 

The security is fine.

We'd like the solution to have more analytics capability.

We would like more detail on reports so that they are easy to understand in terms of usage of data and services. It could be improved.

I've been using the solution for one year. 

It's a stable product. It is reliable. The performance is good. It doesn't crash or freeze. There aren't bugs or glitches. 

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.

We are satisfied with technical support. I haven't used them too much.

Neutral

I've also used Snowflake. 

Azure Synapse is a more integrated platform. With Snowflake, you need to buy it separately and run it off Microsoft. Snowflake, however, has better cost control. Snowflake is comparatively cost-efficient.

It is a straightforward setup. It's easy and not overly complex. I have not measured how long it actually takes; however, I can say the implementation is convenient. My administrator handled the setup. I did not handle it directly myself. 

The solution can get expensive, and it's hard to monitor the costs. It does depend on how you utilize it. You can configure it in a certain way.

I'd rate the solution seven out of ten. 

Microsoft Azure Synapse Analytics is used for analytics.

The most valuable features of Microsoft Azure Synapse Analytics are the interface and the agility of the on-cloud platform.

Microsoft Azure Synapse Analytics's overall integration within the Azure ecosystem could improve. The native Microsoft solution versus another solution, such as Databricks, there are areas where there could be some improvements.

I have been using Microsoft Azure Synapse Analytics for approximately two years.

Microsoft Azure Synapse Analytics is stable.

The scalability of Microsoft Azure Synapse Analytics is very good.

We have hundreds of people using this solution.

Compared to the traditional data center approach, the cloud has pushed forward well for maintenance reduction. There is a 60 to 80 percent reduction.

My advice to others is this solution is not meant for small databases.

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

Our company includes 50 analysts who use the solution on a daily basis to predict customer behavior. 

The solution's best feature is its predictive analytics. 

Integration with other vendors has limitations and could be improved. 

Integration of process analytics would be a nice addition that allows us to analyze efficiency. 

I have been using the solution for six months. 

The solution is stable. 

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

Technical support is very responsive and knowledgeable. 

I rate support an eight out of ten. 

Positive

We do not use other solutions because we operate in a Microsoft environment that is not expected to go to AWS.

The initial setup is complex and I rate it a four out of ten. 

The solution was implemented through a third-party vendor team. 

The solution has helped to predict sales and focus attention on enhancements that have improved the bottom line. 

I rate the ROI a six out of ten. 

I don't know specifics about pricing but I hear that it is quite expensive. For example, Power BI is not as expensive as this solution.  

The solution has superior modeling and predictive analytical abilities in comparison to Power BI. There isn't really an expectation that you would get these superior abilities in Power BI because the solutions have different purposes and use cases. 

I rate the solution an eight out of ten. 

I work in the financial industry where the most important thing is PII so the solution's data masking feature is very useful for clients. 

The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge. A developer will feel at home using the solution. 

The product needs a tool that allows for work from a laptop instead of a browser. When working in on-premises environments, it is important to have all tools installed on a laptop rather than relying on internet connectivity which is a big inconvenience. For example, it would be brilliant to add an integration on Visual Studio to create all pipelines in an offline mode. 

The solution cannot store much data and might require purchasing additional storage. For example if you have 1 TB of data, processing it in the solution will cost ten times more than processing it in Databricks. 

I have been using the solution for seven months. 

The solution's stability is good. 

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.

Support wavers depending on the size of the customer. For example, a Fortune 500 customer will receive tremendous support and quick turnaround time. 

Smaller customers might find it challenging to receive support. 

The initial setup is very easy.

The solution is very expensive because it often requires the purchase of additional storage. Many customers are willing to pay for something that is available in the open source market. If the price of the solution isn't reduced, it will not sell well in the future. I rate the price an eight out of ten. 

Our company heavily promotes Databricks because of the solution's cost impact on our clients. Databricks provides a data lake and a warehouse framework that gives the same or better performance when compared to Synapse, but there is a massive learning curve to using it. Most customers are not aware of Databricks so they don't understand it or use it. 

Two negatives of Databricks are that it is cloud native with no option for an on-premises server and it does not have good integration with any of the IDs. I provided this feedback while I was in training and their team acknowledged the web browser is an issue to resolve. Most developers do not like to work in a browser environment because accidently hitting F5 will cause complete loss or the internet goes down and all changes are lost. These type of issues do not occur when working in offline mode. 

Six months ago, Databricks launched a new product called Databricks SQL that offers multiple platforms such as data engineering with or without a SQL server environment. There is a focus on targeting developers familiar with SQL because the product will only require a different kind of syntax but the SQL environment is still there. Databricks is investing heavily in training developers free of cost and providing certification seminars to increase knowledge of the product as it evolves. 

There are use cases for Azure Synapse with customers who do not want to move away from SQL Server or want a similar experience. The solution offers the ability to create an on-premises server with a SQL syntax that is familiar to developers with no learning curve. Most customers prefer Synapse until they realize the high cost and then they switch to Databricks. 

I rate the solution an eight out of ten. 

I use Synapse Analytics to process data for transformation, create external tables, restrict user access, and for reporting.

Synapse Analytics' best feature is its ability to process large files.

Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node. In addition, the integration with other solutions like Power BI and Azure SQL Database is very slow and leaves a lot to be desired. In the next release, I would like to see a feature to offload Synapse files directly into Gen2.

I've been working with Synapse Analytics for about a year.

Synapse Analytics is fairly stable.

I haven't seen any issues with scalability. 

Microsoft's technical support fails to give us solutions and leaves us to figure out the issue for ourselves.

Negative

The initial setup was straightforward.

I also evaluated Redshift from Amazon, which is much more stable than Synapse Analytics but takes a lot of effort to convert into ORC and load.

I'd give Synapse Analytics a rating of seven out of ten.

We use the solution for integration to enable the data to reuse it in the power gap.

I like the simplicity of the integration of the data and the variety of the language you can use to integrate that.

It offers a straightforward setup.

The solution can scale.

Its stability is good.

There are some limitations. The filing can be improved. Some improvement in the filing is necessary. It needs some kind of growth in the filing development in order to reuse some activities.

I'm pretty new in the company. I started in January. However, they have been using this tool for two years.

The stability is great. There aren’t bugs or glitches and it doesn’t crash or freeze. It’s reliable.

The solution is scalable.

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

I haven't had any contact with technical yet, so I cannot evaluate their level of service.

The solution is easy to set up initially.

I’m not sure how much the solution costs.

We buy direct from Microsoft. Our company may be partners with them.

As Microsoft Azure Cloud, it only has one version. I don't know if there is a version number. 

I would advise users to start loading the data beforehand and understand very well how the tool works and how it's useful. That way, you can evaluate the best solution. Sometimes you need to start to load data and review all the alternatives in the solution.

I’d rate the solution a nine out of ten.

The use case depends on different things. For example, for banking, it would be risk management, fraud, and anti-money laundering. For retail, it would be an omnichannel customer experience. For sales, it could be upsell, cross-sell, retention. It's different for every industry.

The solution is like a marketplace in that it's easy to consume. 

It's scalable; you can scale up and scale down.

The standard things that you see from any cloud perspective make it very attractive.

It is easy to set up.

We'd, of course, always like to pay less for the service if we can.

I've been using the solution for a few years. 

The solution is stable. There are no bugs or glitches and it doesn't crash or freeze. It's reliable. 

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.

I don't really interact with technical support, so I can't really comment on their level of service.

I don't think it's very complex to implement. We have our own expertise. We have our own IPs to set it up and therefore it's not really complex. It takes a week to ten days to have everything up and running. 

Typically, a pool of six or seven people should be good enough in terms of handling deployment and maintenance. Usually, it's comprised of a mix of managers, admins, engineers, and/or developers.

Maybe it takes over a period of two or three years to see an ROI of maybe 50% to 70%. 

I don't deal with the licensing aspect of the solution. 

I'd recommend this solution to other users. 

I'd rate the solution eight out of ten.