Microsoft Azure Synapse Analytics Reviews

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. 

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.

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.

Our company uses the solution to provide data warehousing for customers. Most of our customers are mid-sized. 

Data can be stored any way you want in the data warehouse. Some customers want monolayers which we add with no issues.

The solution is very fast. 

It is reasonably easy to work within the solution. 

The solution should offer a serverless model like Snowflake so you don't have to manage the hyper or operating system layers. 

There are sometimes problems when connecting to the database. Most issues are solved by the community but Microsoft should act more quickly and participate in the process. They should not wait for the community to build a solution before embracing it. 

I have been using the solution for one year. 

The solution is stable. 

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.  

We have not used technical support in awhile but it was okay. 

I previously used Redshift and Snowflake. 

The setup was complex the first few times but we figured out the best way to do it for our mid-sized customers. The setup could be made easier. 

We implement the solution for our customers. 

The pricing is quite reasonable in comparison to other products. Of course, most companies would like the price to be even cheaper. 

Pricing depends on setup but generally ranges from 28,000 to 35,000 Euros per year for a mid-sized company. 

The solution's speed is better than Redshift and Snowflake. 

The solution does take some management. Mid-sized companies would like to work on data instead of hardware or operating system layers. 

It is important to have skilled Azure data engineers to manage the solution. 

I rate the solution an eight out of ten. The solution could improve its rating with an easier setup and more readily-available data connectors. 

I use the solution in my company for graphs. We need graphs for some resources on Office 365. We also do a lot of stuff with other applications, specifically third-party applications. In Microsoft Azure Synapse Analytics, we use pipelines to manage the data from third-party applications.

I love the way Microsoft Azure Synapse Analytics works, and I can also manage Microsoft Fabric. I can gather all the information using Microsoft Azure Synapse Analytics on Microsoft Fabric, including areas revolving around reporting using Microsoft Power BI. I love the way all the application resources from Microsoft can synchronize, help me with a lot of stuff, and reduce the time or hour of having maybe a resource for an hour a day while also being able to use artificial intelligence.

In our company, we always want to improve our data management, including how to manage structured and unstructured data. Every day, we need to do a lot of stuff because we are a bank. We have reports from user accounts and client accounts. Eventually, I want to use machine learning bots, maybe since they can help our company.

I have experience with Microsoft Azure Synapse Analytics.

I am good with the tool's stability part. For stability, I would prefer Microsoft Azure Synapse Analytics over other tools. Stability-wise, I rate the solution an eight out of ten.

It is a scalable solution. Scalability-wise, I rate the solution a seven to eight out of ten.

I rate the technical support an eight out of ten.

Positive

To be able to manage the product's initial setup phase, I believe that you have to know a little bit of networking. On a scale of one to ten, if ten is the easiest, I rate the setup phase as a five or six.

Three people can deploy the solution. A developer, an administrator, and I, the vice president of technology, can deploy the tool.

The tool's on-demand query capabilities help enhance our analytical tasks. I like the way the tool works, as I have people doing queries and an analyst doing a lot of stuff in the product. I love the way that we can manage Microsoft Azure Synapse Analytics.

One person can maintain the tool.

I rate the tool a seven out of ten.

We use Synapse to build views for our data warehouse. It is the place where we get our reports and views. We ingest data into our SQL Servers and Azure SQL, then build all our reporting views within Synapse.

I'm the cloud architect, and I have a two-person DevOps team plus another enterprise architect. Five people are using the interface at any given time. 

Synapse makes it easy to integrate and onboard data from other Microsoft and Azure sources. The interface is familiar because we were using Azure Data Factory before Synapse. It made the transition even easier because the Synapse interface is exactly the same. 

Cost is always the primary pain point. However, we've gotten to the stage where we can set aside finding, and the price is reasonable for our project. 

We have used Synapse Analytics for about a year.

I rate Synapse nine out of 10 for stability. We've had some issues in the past that needed to be addressed, but those were related to how we did our transformations. We needed to learn from our mistakes and figure out how to properly schedule jobs, imports, etc. 

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 

I rate Microsoft support 10 out of 10. We have direct professional support, and they always come through for you if you run into any issues. Our tickets are never open for more than two days. 

Positive

We didn't have anything in place because we implemented Synapse for a specific project. We formulated our use case, considered our options, and decided on Synapse because ware primarily an Azure shop. Using Synapse made sense because it's easier to manage and support. 

I rate Synapse Analytics eight out of 10 for ease of setup. I've set up Synapse so many times in various environments that it's seamless. I have no issues with the product at this point.

We did extensive research and a POC before implementing Synapse Analytics. It took us a couple of days to deploy, including the POC. We had to separate our groups and stuff like that. The second step was to leverage templates for creating the environment. Everything is automated now. If want to do this again, I don't have to go to the portal. I can run it from a template. 

I rate Synapse Analytics seven out of 10. We had to learn a lot before we could get costs under control and budget appropriately. There were a lot of unknowns initially. 

I rate Azure Synapse Analytics eight out of 10. I would recommend Synapse depending on the needs you're trying to address. You need to properly build out your users and see that the technology is going to address your use case. After that, you can make an informed decision about what's best for your company. 

Companies come in all shapes and sizes. Synapse may not be a good fit for one company, but it can work well for others. Try it out first and see if it's appropriate for you.

We use Microsoft Azure Synapse Analytics in several scenarios, we require access to high-performance computing capabilities. This is where the solution proves to be a valuable asset as it offers a node-based solution for computing needs. In numerous cases, we have to undertake intricate data processing operations using the Python programming language, and that's where the solution comes in as an advantageous tool. These are my primary use cases for Synapse. Whenever we need to handle complex data engineering tasks or require significant computing power to accelerate processes, the solution provides the necessary functionality.

The most valuable features of Microsoft Azure Synapse Analytics are its serverless flexibility and complete power have allowed me to explore various different use cases. While I am not an expert in the product, my experience in programming in Databricks has shown me that Microsoft's investments in Synapse could potentially lead to it becoming a complete replacement for Databricks in the future.

In the future, Microsoft Azure Synapse Analytics has the potential to enhance its capabilities by expanding its connectors, specifically with regard to Oracle solutions, such as operating systems. This would involve a comprehensive approach to adding more connectors for both data input and consumption purposes. By doing so, Microsoft Azure Synapse Analytics would be better equipped to meet the diverse needs of its users and achieve greater efficiency in its performance. The provision of more connectors is definitely a crucial area that needs improvement.

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

I have not had any stability or performance issues.

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

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

Before adopting Microsoft Azure Synapse Analytics as my solution of choice, I delved into several other options. One of these alternatives is Snowflake, which I must admit, is a superior choice compared to Microsoft Azure Synapse Analytics. However, it is essential to take into consideration the consumption side when evaluating these solutions. If the consumption side involves Oracle solutions, then an autonomous warehouse would perform better than this solution. On the other hand, if the consumption is within the Azure platform, this solution presents itself as a commendable solution.

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

We have a team that does the implementation.

The solution is worth the cost for our use case, it is worth the money. Despite the fact that there may be room for further optimization of its complete power, the cost-to-flexibility ratio of Synapse is quite favorable. I do not have any specific metrics to support my statement, however, I can assure you that Synapse is not inadequate or disappointing in any manner.

Microsoft Azure Synapse Analytics can be costly, however, a cost-effective approach would be to purchase it in advance through reservation for either one or three years. This will significantly reduce the overall expenses incurred.

After thoroughly evaluating various data management platforms, such as Oracle Autonomous Warehouse, Databricks, Microsoft Azure Synapse Analytics, and Snowflake over the course of the past year and a half, I have come to the conclusion that flexibility is crucial when it comes to choosing the right tool. Microsoft Azure Synapse Analytics stands out as a strong contender, as it offers a unique combination of both traditional warehouse capabilities and modern technological advancements. This combination of features makes Microsoft Azure Synapse Analytics a valuable option and is impressive.

My advice to others is to start with a reserved instance in order to test the waters and make sure it fits their needs before fully committing to using the solution. If, after experimentation, they decide to proceed with using Microsoft Azure Synapse Analytic over its competitors, then I would highly recommend going for a reserved instance to make the most cost-effective and efficient choice.

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

The intention is for the company to utilize Microsoft Azure Synapse Analytics for analytics purposes. The team manages numerous databases and utilizes them to handle multiple tasks.

The most advantageous aspect of Microsoft Azure Synapse Analytics is its simplified data transformation process compared to traditional databases. This makes data cleansing and transformation more manageable and straightforward, which we appreciate. It is much easier to build as well.

The support and price could improve.

I have been using Microsoft Azure Synapse Analytics for approximately six months.

The stability is great.

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

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 level of support from Microsoft Azure Synapse Analytics is average because it takes some time to reach the appropriate person, causing delays. Although we eventually connect with the right person, the initial representative assigned to the call is often unqualified to provide the necessary assistance. They simply repeat what is already available on the website, which we are capable of accessing ourselves. Our goal is to obtain a reliable technical solution, and the turnaround time from the point of contact to receiving a response is longer than ideal. This delay applies to both L1 and L2 support.

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

Neutral

The initial setup took us two weeks at the beginning and now we can do it in less than one week.

The initial setup of Microsoft Azure Synapse Analytics is straightforward.

We accomplished the deployment of the solution by ourselves with the assistance of two architects and four DevOps professionals.

Microsoft Azure Synapse Analytics is an expensive solution and there is a license needed to use it. My company has an enterprise license.

I rate the price of Microsoft Azure Synapse Analytics

We have four DevOp engineers that do the maintenance of the solution.

If your data models are not accurate, and if you are not well-versed in data transformation and model security, the process will be extremely challenging. Thorough planning is essential for the data to be properly managed. You cannot simply execute or implement the process by reading about it. A significant amount of planning is required, including how the data flows will access the data, data security measures, data flow processes, and transformation requirements. All of these aspects must be carefully examined and planned beforehand to avoid complications later on.

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