Microsoft Azure Synapse Analytics Reviews

The solution offers great flexibility and the resource availability is quite good. It's abundant in the market. 

The initial setup is very simple.

The only concern for us is the cost part. When it comes to the implementation and the support and maintenance, we see high-cost implications.

Of course, it varies from use case to use case. Before we get into the implementation part, we have to validate the pros and cons of the architectural components as part of the design and development. Once that's clear, then we'll go for implementation. We might get into technical glitches, however, there are multiple ways to work around them by putting in the right architectural component, which can solve the problem. There is always a workaround.

We've had a couple of interactive sessions with Microsoft already. We have already recommended that they need to strengthen their presence in the data governance part, the data quality part, and then the metadata management, for example, data lineage. We need more data governance to give the flexibility to handle these data quality issues.

It would be great if they update their data features. 

We have been working with the solution for the past one and a half years.

The solution is mostly stable, however, we do experience glitches here and there. We do have solutions that ultimately correct the issue.

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

Technical support is so far, pretty good. It's solving the problem now. Some other clouds are coming in, such as AWS or Google Cloud. They'll eventually be much more competitive in terms of comparatively.

We have used hybrid architecture also. We used the storage part and we have used Snowflake also. Everything is available in one place so that the connectivity issues are solved and you get one component talking to everything. 

It's a very simple setup. it's not overly difficult at all. 

In terms of maintenance, it depends on the scope of coverage and other things. If it is a 24 by 7, we need a set of 14. Depending upon the service coverage and scope coverage, you'll need a certain amount of people. Even that depends upon the scope of the work also. Does the setup require monitoring, for example, or enhancements? Basically, it depends upon the type of contact, and what we get into the AMS projects in terms of the team composition.

While we do not have a business relationship with Azure, we are trying to become partners. 

Most of our implementations happen on Azure itself. Wherever we go, we take the solutions and we go to the other customers and we propose them. We tend to recommend this solution.

I'd rate the solution seven out of ten. There is a scope for improvement. Eventually, as they come across different case by case, they'll enhance things. Currently, what I see here is the data governance part is missing here from a development life cycle point of view.

Microsoft Azure Synapse Analytics differs from the old traditional on-premise business intelligence operations, where it's set up to do real-time analytics. For example, with IoT devices. Instead of having patients come to the hospital and do their operations, the hospitals will give patients an IoT device and you can monitor the patients in real-time using Microsoft Azure Synapse Analytics.

The point of the solution is to integrate the business into the analytics or vice versa. In the hospital example above, traditionally analytics is to tell us what happened. We look at reports to see what has happened. Microsoft Azure Synapse Analytics puts us more on the spot by telling us what's going to happen. Rather than what did just happen.

Microsoft Azure Synapse Analytics could improve its compatibility with Visual Studio. One of the challenges for people moving from an on-premise to a cloud solution, such as Microsoft Azure Synapse Analytics, is that you're constantly working in a browser. There are people that have been working for decades on desktop applications. For them to start working in a browser, it's quite a change. Allowing people to work and do their work inside Visual Studio than in the browser, would be a large advantage.

I have been using Microsoft Azure Synapse Analytics for approximately one year.

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.

I have not used the technical support from Microsoft Azure Synapse Analytics, but I worked with the developers at Microsoft who were top-notch. 

In my proof of concept project, I would simply email Microsoft directly and they were really responsive. The ticketing system on the Azure platform is very good. You just click open ticket, and they will get back to you quickly.

There are not many books on Microsoft Azure Synapse Analytics but there are tutorials and all that information online. However, the tutorials on Microsoft's site are enough to get you started.

The setup of Microsoft Azure Synapse Analytics is different than anything we've used on-site. It is different from the Analysis Services five years ago. However, even though it's different, the setup is easy.

One of the benefits of Microsoft Azure Synapse Analytics is that you shouldn't have to do any maintenance. It's all done behind the scenes. There is a serverless feature, where it'll expand and add RAM and add resources as needed. You have to be careful with the cost.

There's no license required for Microsoft Azure Synapse Analytics. the model is more of a use-based system. You got to pay for computing power and disk storage. Everything has different units and is kept backed up. Microsoft Azure Synapse Analytics uses storage units(SU). This is how everything's computed for cost.

My advice to those wanting to use this solution is to start small to get an understanding of how it operates.

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

We use this solution as a data warehouse. Power BI allows us to visualize the data while analyzing data from the data lake through Serverless. We have not used too much of the pipelines within the Data Factory because we have an isolated Data Factory for that.

This is a stable solution with many functionalities.

The only issue that we have run into with the solution's performance is with regard to concurrency.

We would also like to see faster response times from support.

I have used this solution for three years.

The stability of this solution is good.

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.

Support is good but they could be a bit faster replying to our tickets.

The initial setup was straightforward.

We had one admin complete the initial setup in ten to twenty minutes.

Price varies by use-case. You pay for the database itself in addition to any consumed data within Serverless plus other fees if you use the Data Factory that is inside.

I would recommend others to use this product but urge them to understand that it is more of a technical database used to prepare data as opposed to serving it.

I would rate this solution a seven out of ten.

The product is easy to use. 

One potential area for improvement could be the availability of an on-premises data lake implementation, as the product is currently only implemented in a cloud environment. 

Additionally, the possibility of integrating data from multiple sources could be beneficial. 

We have used Microsoft Azure Synapse Analytics for approximately three months.

The platform's scalability is similar to that of SQL databases. It requires developing components, implementing services, and performing other related tasks.

The initial setup process is straightforward. 

My advice would be to remain open to learning new things, particularly because working with Synapse Analytics requires a shift in mindset from traditional tools like SQL Management Studio to newer tools and approaches.

I rate it an eight out of ten. 

The most valuable aspect of this Microsoft Azure Synapse Analytics is its consolidation of technical support from Microsoft, and its ability to securely host large quantities of data within the cloud environment. The overall ability to manage and maintain Big Data within the cloud provides a heightened level of efficiency, reliability, and support from Microsoft. This results in a superior user experience and an increased level of value for the end user.

There may be some challenges in terms of connecting with Virtual Networks (VNETs) to Microsoft Azure Synapse Analytics.

I have been using Microsoft Azure Synapse Analytics for approximately one year.

The stability of Microsoft Azure Synapse Analytics is great. It offers a high level of performance.

The scalability of Microsoft Azure Synapse Analytics is good.

The support from Microsoft Azure Synapse Analytics is excellent.

There is a steep learning curve to do the implementation.

I rate the initial setup of Microsoft Azure Synapse Analytics a seven out of ten.

The entire Microsoft Azure ecosystem is well connected and Microsoft has done well with the features.

My advice to others is to try out the solution, do your homework and research, and set up a POC environment.

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

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. 

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.