Microsoft Azure Synapse Analytics Reviews

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.

We use this solution to create data pipelines and to improve the self-service environment for end users. We use all the functions of Microsoft Azure Synapse Analytics.

I like the keynotes and their simplicity. Like other Microsoft products, Microsoft Azure Synapse Analytics is simple to understand and use.

The linked services can be improved. We can create dynamic linked services to access a lot of databases but only those of the same type. For example, I can use the same linked services to access 11 SQL databases. However, if I have 11 SQL databases and five Oracle databases, I need two dynamic linked services. I cannot do it with only one linked service.

The UI also needs to be improved. When I have used Azure Synapse for programming with PySpark, Scala, or .NET, for example, the UI has been unstable. If I open two notebooks for programming, one notebook will queue the session of the other.

I've been using this solution for two years.

I would rate the stability at eight out of ten because Microsoft Azure Synapse Analytics is unstable during programming. 

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.

Technical support staff are knowledgeable. Whenever we have needed support, they have had a good process and have always had the answers we needed. I'd give technical support a rating of ten out of ten.

Positive

The initial setup is simple, and I would rate it at ten out of ten.

The pricing is competitive, but only when you pay upfront. If you pay as you go, it's not as competitive. I'd give pricing a rating of seven out of ten.

On a scale from one to ten, I would rate Microsoft Azure Synapse Analytics at eight.

We're using this solution for general data integration. We are customers of Microsoft Azure Synapse Analytics and I'm a data specialist. 

I like the solution because it's very interactive and provides flexibility. It's mostly a drag-and-drop procedure. It also provides a lot of design choices.

We've only recently starting testing this solution and it would be helpful if the documentation was better or if the company could provide some kind of presentation to help us understand how the tool works and what's required to optimize use of the solution.

We've been testing this solution for a couple of months. 

I haven't seen any issues with stability or scalability. We have an infrastructure team of around 40 people. 

The company chose Synapse Analytics because the price is fair and I understand it's cheaper than Snowflake.

We're also hoping to evaluate Snowflake which is an advanced version of both Azure and AWS together. Snowflake has advantages, especially in terms of scalability which can also be implemented separately at the storage level and also at the computer level. 

I think Synapse Analytics is definitely better than the traditional high solution data solutions that we've previously used. It's definitely worth considering and I haven't come across anything negative, only advantages for now.

I would rate this solution an eight out of 10. 

I work with Azure Synapse Analytics, Power BI, and Premier as a data administrator, using Microsoft's Azure cloud infrastructure. Azure Synapse Analytics is the principal data administration tool for our internal data warehousing, but we also use it for our customers' data warehousing and analytics in different industries. For data entry, we use Microsoft Power BI.

Internally, we have about 200 personnel currently using Azure Synapse Analytics, including data specialists, service managers, and other tech workers. It is not extensively used by all, however, because we don't often use it for very large amounts of data, except where financial data is involved.

Azure Synapse Analytics helps us move quickly when it comes to finding data warehousing and analytics solutions for our customers.

We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for different sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on.

It is our main data warehouse solution, and the one big feature I appreciate is all its various analytics functions. The built-in analytics also makes it an attractive option for our customers, where we act as a service provider for them.

Unfortunately, we have had some issues with the dashboard reporting. Sometimes, the data for specific periods would just appear blank on the dashboard. To investigate this, we worked with a Microsoft incident agent and it turned out to be a result of bugs in the platform when dealing with specific types of queries in Azure Data Factory.

We have also encountered some bugs regarding incompatibility with certain versions of Power BI. In the past, Power BI used to integrate nicely with Azure Analysis Services which we used as a bridge between Power BI and Synapse Analytics, but they have since discontinued the features that worked so well for us.

Apart from fixing bugs, I would also suggest:

• The learning features and documentation could be improved and expanded on.
• The calculation and forecasting tools could be made more clear and easy to use.
• The price could be lower.
  

I have been using Microsoft Azure Synapse Analytics for one and a half years now. 

When it comes to stability, Synapse Analytics has suited us well, because it's very fast, i.e. it has good performance. Compared with the on-premises SQL solutions we've used, the results are two times as fast.

There are some bugs that we've encountered with the platform but we are able to work with Microsoft directly to resolve them as they come up.

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.

In our context as service provider, normally we have direct contact with the server. But in some cases, we have needed extra support which was very slow.

For technical issues, I often solve them myself using Microsoft's learning resources and support forum.

For me, it's the fifth data warehouse I've used. Other specialists here also use other warehousing solutions based on SQL but for the moment Synapse Analytics is the best overall solution for us primarily because of its ease of implementation and flexibility.

Because I was not familiar with the solution beforehand, the initial setup was quite complex. I had to learn a lot in the beginning stages. I'm grateful that there is help to be found in the Microsoft forums, however, and there are also options to study for certifications that help you learn how to use the platform properly.

It took approximately six months to implement Azure Synapse Analytics in our organization. We set up the data warehouse features for internal use across 200 users, including data specialists, service managers, and tech workers who manage our own data and also our customers' data.

For the main deployment, we used a third-party support provider in Chile who helped us greatly.

We normally pay between $300 and $500 per month, which is quite expensive for how much we actually use it, performance- and usage-wise. They have a cheap version and an expensive version, and our usage usually falls in the middle ground, which makes it not as cost-effective as it could be.

We evaluated on-premises SQL solutions for data warehousing, but our main motivation for using Synapse Analytics instead is that it lets us come up with and manage customer solutions very quickly. Some specialists are still using other SQL solutions as well, however.

There is always room for improvement with Azure Synapse Analytics, but for our use cases it works very well. 

I would rate Microsoft Azure Synapse Analytics 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. 

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.

 I'm a senior consultant.

For those working in the retail sector, this product can capture all the transactional data throughout a company's stores, process them, and put them into the Azure Synapses. Once you have the data, you can clean and aggregate it. On top of that, it has a reporting tool so you can connect to those Data Warehouse Synapses and pull up your reports which can then be used to prepare the dashboards and enable more insight.

Non-structured data is unavailable with this product. 

The solution is stable. 

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.

The customer support is generally quite good. They follow up relatively quickly although it can sometimes take more time if it requires an SOP to follow up. 

The initial setup is straightforward. It's a matter of connecting to your visual studio or management studio.

It's important to understand your business needs and choose an appropriate solution based on the industry you work in and what needs to be achieved. There are a lot of tools available on the market, it's important to get the right one. 

I rate this solution eight out of 10.

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.