Microsoft Azure Synapse Analytics Reviews

We have implemented it for two solutions - data warehousing and BI Synapse (Business Intelligence). We also use it for merchandising, where based on our booking patterns, Synapse is used to analyze and target customers with more products. We use it for virtualizing, and BI is for analyzing business strategies.

The best thing about it is that it has integration at multiple places. It can talk to more than 90 types of data sources, which is one good thing about it.

There are some limitations based on the fact that it is a new platform. Some of our users have recommended switching to a different platform they are more familiar with. However, from an infrastructure standpoint, I believe it can be more secure in terms of availability.

Currently, even though we have locked down public access, the Synapse can still be viewed with the URL without VPN access. It only allows viewing the configuration and not any sensitive data or pipelines. We are working with Microsoft to address this issue, but it seems like they have recommended that it be open, and there is currently no solution. Perhaps there will be improvements in other aspects in the future.

We have been implementing and working with it for about a year now.

It's quite stable. So far, we haven't experienced any failures. If any failures occur, it will be due to the type of data or changes in it. But apart from that, the pipeline runs fine. We are getting our data reports that the team runs from Power BI. So everything seems to be stable so far.

We are premium customers. So, we have access to their top-tier team. I can say it's pretty good.

Positive

It was very complex, but we have grown out of it now. We have at least six environments only on Synapse.

This is the first solution that we are trying out. But if we plan to compare it with another solution called Snowflake, it will open up more dimensions for our thoughts to work. 

However, based on what we have achieved so far, I can rate it as an eight out of ten overall.

We primarily use it for data transformation purposes, as well as for storing data. Additionally, we use it to connect to Power BI for reporting purposes.

We find the serverless tool the most valuable feature we're currently exploring.

One area for improvement could be better integration with Power BI, as well as data integration with BW. If we could find a connector or process to export data from BW into Azure, that would be helpful.

I have been using the solution for two years. I'm currently using the latest version.

We are just building the solutions, it's like the solution is very much immature. We are setting up those things. So as of now, it's not stable.

I would rate the stability a five out of ten.

The solution is very scalable. We are a medium-sized enterprise, and there are almost 4000 end-users.

We are getting good support from Microsoft.

Positive

I would rate the initial setup a seven out of ten. The initial setup was good.

We are currently working with around five or six people for the deployment. Moreover, about four or five people are needed for maintenance.

I would rate it a four out of ten, where ten is for most expensive.

I would recommend using Microsoft Azure Synapse Analytics because it includes everything from integration to transformation and storage.

Overall, I would rate the solution an eight out of ten.

We are using the solution to process a large volume of data. We are taking advantage of the MTPP functionality feature in Azure Synapse Analytics and connecting our reporting dashboard to its dedicated support tool. These are the two primary use cases we are currently leveraging.

Generally, people have differing opinions on whether to use Azure Synapse Analytics or Azure Databricks. These are two different services from Microsoft, and customers often struggle to decide which is best suited for their particular use case. Both services have some features in common and some that are exclusive to one or the other. It is a trade-off and ultimately depends on the use case that best serves the organization. Incorporating the features of both Azure Synapse Analytics and Azure Databricks would meet most use-case scenarios.

The cost of the solution has room for improvement.

Azure Database has a very good Unity Catalog functionality, which is a form of governance within Azure Databricks. Similarly, for Azure Analytics, having a governance product would be great. However, Microsoft already has Azure Purview, which is meant for governance, but it would be nice to have that functionality built into Azure Synapse Analytics.

I have been using the solution for seven years.

The solution is stable.

The solution is scalable. Generally, the development team of around 20 people uses Azure Synapse Analytics directly. Otherwise, a Power BI dashboard accesses the Azure Synapse Analytics database, and the end user uses the Power BI reports, not being directly exposed to Azure Synapse Analytics. Only the development and software development teams use Azure Synapse Analytics.

We are always in contact with the Microsoft team. We keep up to date with our Microsoft reference architecture and other related matters through our communication with the Microsoft team members.

Positive

The initial setup is straightforward. We can have the dedicated SQL up and running within 15 minutes.

The implementation is completed in-house.

The cost of the solution depends on the type of license we choose, such as pay-as-you-go, one-year reserve, or three-year reserve. The cost varies depending on the options selected and can be very expensive.

I give the solution a nine out of ten.

Depending on the organization's use case, there are multiple options available. For example, if the workload is medium, there are different products available such as Azure SQL Database for small or medium-sized data, and Azure Synapse Analytics for extremely large volumes of data. Ultimately, it is the use case of the organization that will determine the need for these particular services.

We use Microsoft Azure Synapse Analytics for a combination of a data warehouse with some advanced capabilities, to allow us to run some machine learning models on top of it. 

The most valuable feature of Microsoft Azure Synapse Analytics is the capabilities, and the integration with other Azure resources, such as Data Factory, Databricks, and Spark for data processing. The overall ability to compose the solution with other Azure resources is valuable.

Microsoft Azure Synapse Analytics could improve in usability. I have found the same issue with all Microsoft solutions.

I have been using Microsoft Azure Synapse Analytics for approximately 10 months.

Microsoft Azure Synapse Analytics is stable.

The scalability of Microsoft Azure Synapse Analytics is very good.

We have approximately 40 people using the solution. We have plans to increase our usage in the future.

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

Neutral

I did not use another solution prior to using Microsoft Azure Synapse Analytics.

The initial setup of Microsoft Azure Synapse Analytics is straightforward. The full process took a couple of weeks when we started and finished.

We did the implementation of Microsoft Azure Synapse Analytics in-house.

We have a cloud services team with approximately three or four people and they take care of everything we need to support Microsoft Azure Synapse Analytics.

It's difficult to compute a return on investment in data analytics.

The price of Microsoft Azure Synapse Analytics can vary. Other solutions are typically fixed prices and a fixed cost regardless of usage, but this solution is based on usage or consumption.

The best comparison for Microsoft Azure Synapse Analytics would be with or against Snowflake. The only difference is that Microsoft Azure Synapse Analytics is more modular. If you want to build something very complex, you can. However, if you want to do something simple, you could stick with easy-to-use, more integrated platforms, such as Snowflake.

My advice to others is they should leverage other Azure components if they can. If they are looking for an integrated solution that's easy to use, they should look at competitors.

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

I use Synapse Analytics to process data for transformation, create external tables, restrict user access, and for reporting.

Synapse Analytics' best feature is its ability to process large files.

Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node. In addition, the integration with other solutions like Power BI and Azure SQL Database is very slow and leaves a lot to be desired. In the next release, I would like to see a feature to offload Synapse files directly into Gen2.

I've been working with Synapse Analytics for about a year.

Synapse Analytics is fairly stable.

I haven't seen any issues with scalability. 

Microsoft's technical support fails to give us solutions and leaves us to figure out the issue for ourselves.

Negative

The initial setup was straightforward.

I also evaluated Redshift from Amazon, which is much more stable than Synapse Analytics but takes a lot of effort to convert into ORC and load.

I'd give Synapse Analytics a rating of seven 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.

I am the Associate Director of a company that is a partner of Synapse.

The solution offers strong scalability opportunities.

I would like to see more ready-to-use products from Synapse. Right now, everything seems a bit futuristic without much modern use.

The solution is scalable.

Price is dependent of the use case of the customer. Customers are not likely to only use this as an individual platform/database, they are likely to bundle it with the Azure stack.

Snowflake is a solution that is much more ahead of the game. There are many gaps in Synapse that Snowflake has fulfilled (i.e. usage, and storage).

Be sure to be clear about the ideal pipeline for Synapse, differentiate your needs, and validate based on use-case.

I would rate this solution a six out of ten overall.

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.