Microsoft Azure Synapse Analytics Reviews

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.

We are an IT service provider. We develop solutions for our clients and this solution is used in some aspects of that.

The dashboards are good.

We haven't had any issues when it comes to customization.

The security seems to be okay. It hasn't given us any problems and we don't feel insecure.

The pricing seems to be quite fair.

I know their roadmap, and I am looking forward to what they have already published.

We've been happy with the level of reporting and documentation on offer.

There aren't any features that are really lacking in the solution. We don't really have any issues with it in its current form.

When we used the on-premises deployment model, we had data latency issues and suffered from page performance problems. However, since we've moved to the cloud, we haven't had these problems.

The initial setup has a bit of a learning curve.

We've been using the solution for the past 18 months so far.

The solution seems to be scalable. We haven't had any issues with bugs or glitches. It doesn't crash or freeze. It's quite good.

The scalability has been pretty good, in our experience. We have been able to scale it twice to the number of users we needed. We were also able to double the amount of data load. We haven't had issues. If a company needs to expand, it should be able to do so without problems.

We've dealt with technical support and have found them to be quite responsive and knowledgeable. We're quite satisfied with the level of support we have been getting so far. They're helpful.

It's hard to gauge the difficulty or simplicity of the setup. For our company, we were learning the processes as we were doing it. In that sense, it was challenging due to the fact that we had to learn and then do. After a period of time, we were able to get comfortable.

We handled the implementation ourselves. We taught ourselves about the process as we went.

We pay a licensing fee on a monthly basis. We find the pricing to be fair among the competition.

We're just end-users and customers. We don't have a business relationship with the organization.

We're using the latest version of the solution right now.

I'd recommend the solution to other organizations.

I'd rate the solution at a nine out of ten.

I work for a consulting firm, with many different use cases.

Synapse DW is for traditional data warehousing with a large amount of volume, that requires you to do reporting.

In terms of Synapse Analytics, I haven't put it in yet, but I'm looking at it for kind of one-stop-shop or Swiss Army Knife type projects. They've been asking for a factory or creating something that connects to the cosmos to turn it into analytics reportings, just sort of needless connecting and just making it easy from a developer standpoint to deliver on any sort of business analytics that needs to be done.

I think the most valuable component is that pipelines are built into it and then the feature that you can mirror a cosmos BB for analytics.

I think that there should be better governance. Actual pipeline level security, if you create a pipeline within the tool, because it's a one-stop-shop for everything, you control who has access to what, and that goes for anything, whether it's an internal or an externally managed table. 

I think there needs to be an improvement with support for external tables supporting Spark, but further support of Lakehouse to make it a true data warehousing product where you have this true separation of computes and you have a separation of storage. 

I think it kind of dips its toes in there, but in order to achieve, I think with a vision that Microsoft is doing, trying to get at to replace Bolt, but compete with Snowflake and Databricks at the same time, it needs to have those features on.

In the next release, I would like to see Lakehouse and better governance.

I have been using Microsoft Azure Synapse Analytics for six months and Synaps for a couple of years.

It's a very stable solution. We have not had any issues with the stability of it.

For its traditional data warehousing, it's scalable.

For Synapse Analytics, I am uncertain about being able to trust it with large volumes, which is what you would expect with Databricks.

There are only three or four people in our organization who do this type of work.

We directly work with Microsoft in everything, so they're very responsive for us and they're definitely very committed to that product.

It's a complicated product.

I am a consultant. I implemented the solution myself.

It's very difficult to price unless you know exactly how the customer is using it.

I would recommend this solution to others who are interested in using it.

I think it's definitely something that they should consider. It's come a long way from where it started. 

It's just finished out a public preview and it's great if you're looking to combine a lot of tools into one and you're running a smaller shop. I think it's a great tool.

I would rate this solution a seven out of ten.

We are mainly using this solution as an interface between the Data Lake and the users.

We are consultants and this product assists with the services that we offer for our clients. Our company has a large number of consultants who are working in this space.

The most important feature for me is the integration with PolyBase.

Other valuable features for me are advanced threat protection and data privacy.

I would like there to be more focus on the Software as a Service (SaaS) product. For example, Snowflake, one of their competitors, is more focused on SaaS.

They need to improve a little bit in terms of user-friendliness. I would rate them a three out of five, in terms of how user-friendly the interface is.

The auto-scaling capabilities are quite poor, especially compared to Snowflake or Firebolt.

In total, I have been using Microsoft Azure Synapse Analytics for one year.

This is a stable solution.

You can scale it, although you need to put in more effort. We have approximately 800 users.

In general, Microsoft support is pretty good.

I have experience with similar products such as Snowflake and Firebolt.

The initial setup is very complex compared to other products. It takes weeks to deploy.

We implement this product for our clients.

The cost of the licensing depends on the size of the warehouse, where the cost of storage is approximately $130 USD per terabyte. The charge might be several thousand dollars or more each month.

There are multiple options that are available at an extra cost. For example, the advanced threat protection costs an extra $25 USD.

We evaluated several options before choosing Synaps Analytics.

The suitability of this product really depends on the use case. It is good if your company is using only Microsoft products and you don't want to use another stack. If you want to use other platforms then you should consider Snowflake, which is also deployed on Azure. It really depends on what it is that you need.

I would rate this solution an eight out of ten.

We are a consulting agency and the Microsoft Azure SQL Data Warehouse is what we use for general BI reporting and visualization.

The most valuable feature is that you can suspend the computer if it is not being used, which means that you don't incur costs. This is better than Amazon Redshift, where the costs continue to accumulate.

The documentation is good.

This solution needs to have query caching so that if the same query is run and the results are available, it will return the data from the cache without having to re-run the query. As it is now, you still have to use compute for each query.

We would like to have integration with the data lake so that we can avoid retrieving the data from it, just to store it in Synapse before we can use it. From an architectural perspective, avoiding this replication would be good.

I have been using this product for about one year.

Stability-wise, this is a good product.

This solution is scalable, although I don't expect that we will expand it beyond the current usage.

We have not had to reach out to support. Rather, we have relied on the documentation. It is easy to solve your own problems.

I also have experience with using Snowflake. It has the option to cache query results, which is helpful. 

Amazon Redshift is another similar solution that I have experience with, although it lacks the ability to suspend the computer to save costs when it is not being used.

The initial setup is straightforward.

The Azure SQL Data Warehouse has been renamed to Synapse, although not all of the features have been implemented yet. I am looking forward to a more mature version of this product in the future.

I would rate this solution a seven out of ten.

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.

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.

We use this solution to analyze big data. We collect data from different sources then we analyze that data with Synapse.

One of the most valuable features of this solution is its ability to integrate well with other services offered by Azure. 

Scaling this solution up and down is not quick and easy. This could be improved. The pricing of this solution could also be improved. 

We have used this solution for two years. 

This is a stable solution but we have experienced some unavailability issues. These were not critical issues. 

This solution is quite easy to scale depending on your workload. Overall it is a little bit expensive. You have to know exactly what you are doing as you scale up, otherwise the cost goes up quite quickly.

This solution is relatively easy to set up and use. The time it takes to setup depends on the complexity of your environment. If you want to complete a basic setup, it only involves a few clicks. In a production environment for a complex setup, it's it takes some time to complete the configuration. 

We completed the setup in-house. 

Synapse is useful for very big loads of data. 

I would rate this solution a seven out of ten.