Microsoft Azure Synapse Analytics Reviews

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. 

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.

This is a data warehousing solution.

The most valuable feature is the scalability. It scales out, so you can build a large database and not have to think about whether it performs, or about connecting to the servers to become larger.

There are several specific features and functions available on the on-premises version that do not work with the cloud version. There are many issues regarding migration.

They are building it more and more, but if you have the same version on local you cannot just go to the cloud because some of the functionalities don't work yet. You would have to re-code everything, and maybe even do it differently.

In terms of documentation, they can make it easier or start with some advising or instruction. As it is now, it's like making a puzzle.

Technical support needs some improvement.

They will need to include some features for the Cloud version.

They can make subsets of the database so you can schedule the marking department to work only between nine to five, but ETL can run at night. 

With a subset database, you can cut costs, similar to Snowflake whose price is a lot lower.

This solution is stable.

This solution is scalable.

We have a couple of administrations using this solution and the rest are indirectly using third-party tools. They are developers and administrators.

The support is difficult. I don't think that their support is good.

You can call for help, they take your request, but they don't have an understanding of the tool.

You have to wait a couple of days for someone to call you back.

There have been times where I knew more than they did, so you have to figure it out for yourself.

I am not satisfied with the support, but I do understand that when you have a service desk or a help desk, they cannot go through the entire solution. What I expect is that the second line should, but they don't have a second line.

You submit in a support ticket and three days later you get a callback and have to explain the problem that you are having again. It takes more time.

I have called Microsoft and even they were not sure and nobody could really help me.

The initial setup for me was straightforward, but I have a lot of experience. I think that for some people who are less experienced it would be complex.

It's not just the documentation on what version you need to have and what pricing. It is really difficult.

You have to read a lot to understand what you are doing.

This solution starts at €1000.00 a month for just the basics and can go up to €300,000.00 per month for the fastest version.

It's pay as you go, so you never know what your bill is going to be beforehand, and that's scary for customers. If you have someone who makes a mistake and the program's a loop that is running all night, you could receive a very expensive bill.

The bad side to pay as you go is that sometimes it can stop the enthusiasm of the data scientists, as they are afraid to run a query because they are afraid of the bill and how much it will be.

It's a nice solution for a simple data warehousing, but it's still an immature solution.

It is stable but it takes a lot of time. 

Smaller companies have better products, but the problem will always be there and the smaller company will not survive.

Customers will have tools that are not supported anymore.

Microsoft is so big that people trust them, they will eventually get there but it will take time to get the features with quality. There are, however, some solutions available that are better and cheaper. You can purchase them instead of having to reprogram everything that you have already done.

My advice would be to compare this solution with others. Snowflake would be a comparable solution. It's cheaper, faster, and better.

I would rate this solution a seven out of ten.

Our general use of this solution has to do with the needs of one of our clients. They had an SQL server and they were migrating from an on-premises SQL Server to Azure SQL server on the cloud. We use this solution because it fits their budget and they have some clients in other countries they want to give access to the product through Power BI.

What I like the most would be MPP (Massively Parallel Processing) architecture. Because we had to migrate a lot of data and it helps us a lot to make things faster.

As far as improvements to the product, I think the Data Factory integration should be enhanced to be properly implemented because right now it is still lagging behind other vendors like Informatica. We ended up having to use Data Factory because we don't have any expertise in Informatica. But I want to see Data Factory get better overall.

An enhancement I would like to see is in data loading for Data Factory. Right now we are seeing a little bit of a performance lapse in the cloud server. Specifically, this happens between Azure and our clients maybe because we are connecting to SQL Server Management Studio. There is a slight but noticeable delay. I do not know if it has to do with Azure and whether it is their problem or our problem.

I can't complain much about Data Factory, but because I used to use SSIS (SQL Server Integration Services) which was the prior on-prem version, I know what capabilities it is missing in comparison. They changed it over to Data Factory, but by comparison, Data Factory has a long way to go to reach the level of SSIS as a product.

Right now is still early in our implementation so I can't really say that I am sure it will remain stable in production under larger loads. But so far it is good and we are happy with the solution and its stability.

One of the reasons we decided to go with Azure was because we knew we could scale-out. We were happy with this scalability before we committed to the product.

Right now, I know only two of our clients are using the solution. They are actually a government organization. But we know we can scale up when we have to.

I have not had direct contact with technical support. Someone else handles that. But I have not heard any complaints.

The initial set up was not very complex. It was easy to install this product.

We had a partnership with another team and together we did the installation. They helped us to figure out some architectural decisions which they were very helpful with.

My advice to other people considering this solution is that this is a great product. But there is one problem and that is the rate that Microsoft is changing its software implementations. The rapid changes could make it hard to keep up with upgrades. Some of the features get enabled and disabled very quickly. So we are waiting now until everything settles down because cloud technology is still evolving. We understand that. But, on the other hand, as they make so many changes to keep up with the technology, it remains hard to predict what the future of the product is. I might say to anyone that they wait for some time in 2020 and then start using the product.

On a scale from one to ten where one is the worst and ten is the best, I would rate the product as somewhere between a seven or an eight. If I have to choose seven or eight, I would pick seven-out-of-10.

We encountered data processing and transformation issues while working with Apache Spark languages for the product. This particular area needs improvement. 

The product's error messaging could be friendlier. Additionally, the monitoring process using Azure ML SDK and Python should depend on the data for the results. Along with the documentation, they should provide essential training for proficiency in CLI. It will help in better monitoring.

We have been using Microsoft Azure Synapse Analytics for two years.

The product is expensive.

I rate Microsoft Azure Synapse Analytics a seven out of ten. It is a fantastic product; we are satisfied with its features and performance. However, there could be more information available about the platform.

Microsoft Azure Synapse Analytics can be used for analytics and brings together data integration.

The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit.

Microsoft Azure Synapse Analytics can improve querying. I have recently used Microsoft Azure Synapse Analytics to connect to the Delta Lake file and I have noticed some issues. It has not been able to read the latest version of the Delta Lake file and I have found this to be a disadvantage that they can improve.

In the future, Microsoft Azure Synapse Analytics could improve the performance, there are other solutions that are better, such as Databricks.

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

On the client's side, there are approximately 100 users of this solution.

Have I reached out to Microsoft technical support in a few instances and we have raised a couple of tickets. A couple of agents have been knowledgeable, but not everyone is.

The installation of Microsoft Azure Synapse Analytics was easy. It was not complicated, but I have not explored the VNet Injection or the Private Endpoint though I think it would be straightforward.

We are on a monthly payment plan for the use of Microsoft Azure Synapse Analytics.

We have done some comparisons between Microsoft Azure Synapse Analytics in many areas, such as processing queries, versus Databricks. We have found Databricks to be better in performance.

I would recommend this solution to others. The client that I am working for, their preferred database is Synapse.

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

We have implemented our data warehouse on Synapse.

The solution has been reliable so far.

The product is scalable, or, at least, that is my understanding. 

We've had a good experience with technical support in general. They are helpful. 

The solution has proven to be very user-friendly.

Right now, we are really struggling with the performance. it's not as good as we had hoped. 

I cannot recall coming across any missing features. 

One problem is that getting the query cost is not easy. I need to use multiple tools. It can be accessed through the web, or we have Azure Data Studio, or SSMS, and I only get the query cost in SSMS, the SQL Server Management Studio. In other tools, I'm not getting it. For example, in the web version or in Azure Data Studio, it is not available. They need to make it accessible in both of those places as well. 

I haven't used the solution for very long. 

The performance on offer is lackluster. We were hoping for better. 

That said, it is reliable, and if I get the required performance, I am happy with it. 

While I haven't really tested the scalability, it is my impression that the solution can scale and it shouldn't be an issue for any company to do so.

Technical support is good. They are helping us in improving the performance. We're quite satisfied with the level of service they are offing us. They are helpful and responsive. 

I did not handle the initial setup. That was handled by another party. Therefore, I don't have any insights into the process or how easy or difficult it was to implement. 

I don't have any insights into the licensing process. It is implemented on our client's side, and therefore, I'm not involved in that.

We're just customers and end-users. My company does not have any relationship. It's our client who has a relationship with Microsoft.

I'm not sure which version we are using, however, I would guess it is the latest version. I'm not 100% sure.

Since the solution is still new to me, and I am having issues with performance, it's too early to say if I would recommend the solution to other users or companies. 

I'd rate the solution at an eight 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.