Microsoft Azure Synapse Analytics Reviews

We are service providers for our clients.

My clients primarily come from the enterprise segments, such as manufacturing, retail, pharmaceutical, and industrial. Most are supported by a large ERP solution like SAP.

Some of our clients are mid-size and others are large enterprise companies, some of the largest in India.

Some of the most valuable features would include Familiarity for practitioners like us and also familiarity for the businesses. SQL servers have been around for several decades and there are many who are familiar with SQL servers, such as SSIS and SSRS.

They are available on the Cloud, and the platform is very intuitive.

It integrates very well with Power BI, which I would rate as the best self-service BI. All the data warehouses eventually end up in BI or Machine Learning. 

Instant Apps that are more integrated rather than desperate components. You need to get different components engineered together, and with SQL everything comes together.

Instant Apps is a combination of your Spark compute platform, your SQL data platform, and your object storage. It's a platform that is integrated all together. 

It's easy to work with a faster turnaround time on my project deliveries.

Also, the integration with Power BI self-service is much, much easier and familiar.

You can have several SQL servers, they have large .NET artifacts that combine various components together very well.

What I would like to see more and more of in Azure is its support for IoT and streaming media information.

It needs strong support for social media, internet data, and native support for NoSQL. At this time, it works very well with the structured data

Stability could be improved.

Technical support is very good, but could also be improved.

My company has been working with SQL Data Warehouse for approximately three and a half years, and I have been working with this solution for one and a half years.

In the last six months, there have been a couple of incidents. We have experienced som outages. One of our clients was in a blackout for a couple of hours. Most of the clients in India have experienced outages also. They were restored, so I refer to them as glitches.

In principle, it's a limitless, serverless solution. As long as your region has resources, you can go on expanding. We have not had any problems with scalability.

Microsoft Azure comes integrated with Databricks as a Machine Learning platform, it's highly scalable.

Technicals support engages very well. We have account managers in place who correspond with technical support. 

The technical support team has a good relationship with our Account managers.

If we have an issue, we advise our account managers and present the ticket, they contact Technical support and resolve the issue very quickly.

If however, I have to contact Microsoft technical support at the backend, they are not very knowledgable. They have a good understanding of their products, but most of the time they struggle with that.

The initial setup is easy. The learning curve for Microsoft platforms is very low. An engineer with very little experience would be able to complete the initial set up with ease.

It has a quick turnaround time. We have completed the deployment in weeks.

For a BI project scheduled for six months, within the first month we would have completed the data warehouse installation, and the remaining five months would be for building the content, the data pipelines from the sources, the semantic models, and the BI.

When you compare it with other solutions that take months to get your sandbox running or to get your development running.

They are cost aggressive, and it integrates well with other Microsoft tools. For example Downstream and Teams.

We use the serverless platform as a service, that is only available with Microsoft Azure.

You don't have to hire experienced engineers to set up and implement the solution, saving you money, because it is very intuitive and the turnaround time is very low compared to other data warehouses. I would put it in par with solutions such as Redshift and BigQuery.

It's very modern, easy, and intuitive.

Most of the services are cheaper than other vendors.

This definitely falls into one of the top three or top four solutions and platforms in the world. I would definitely recommend it. If someone should ask me if they should use Microsoft Azure SQL Data Warehouse, I would say yes.

Personally, I don't see one great solution that exceeds in all aspects. Every solution has some good points and I think they have very beautifully found their strength and they're building upon it.

When asked what would best suit me, I would assess their environment requirements and could easily recommend any of the top four, being AWS Redshift, Google, Big Query, and Microsoft Azure.

I would rate this solution an eight out of ten.

We primarily use this solution for source analytics and procurement.

The most valuable feature of the solution is the analytics and that it can connect with Power BI. I found it quite interesting and very compelling in terms of detail within a single stack.

I would like my team to be able to build pipelines that integrate with the Azure Data Factory. Some of the best-in-class ETL products that are available in the market, such as Informatica ETL, are far more mature than this solution.

We started implementing projects with Microsoft Azure SQL Data Warehouse about six months ago.

This is a stable product.

Scalability is good and we haven't had any issues.

We have approximately 150 users. We are stable at the moment but we will expand our usage as we get more data.

We have contacted Microsoft support twice, but I do not have much experience with them.

In addition to Azure SQL Data Warehouse, we work with the version that is on-premises.

We are also working with Oracle Data Warehouse and we plan to continue using both of these solutions.

The initial setup is straightforward.

We implement this solution for our customers.

If you are using Microsoft products, such as Office 365, then this solution is good because it can take the data from multiple sources. 

This is a good product, but when you compare to Oracle Data Warehouse there are differences in scalability, high availability, and implementation.

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 Microsoft Azure Synapse Analytics for analytics.

If I'm looking for something good in the cloud, I would want it to have better standard connectors.

I have been working with Microsoft Azure Synapse Analytics for two years.

We are up-to-date with the latest version.

I have been working with Microsoft, and they have been very helpful.

It's the only product I've used. I'm not sure what's wrong or what could be done better.

I don't know about the price, but I'm trying to get a sense of the cost. I believe having a good comparison would help.

This is the only product I've ever used, as such, it's extremely difficult for me to say anything about it. For example, if I needed a bike, and now I have one and am riding it. If you ask me some questions, it's difficult for me to say, "Oh, I really missed this one on my first bike," unless I've ridden a few bikes. I'm not sure why everything is the way it is. I had a need, and I'm only using it now.

I'm trying to understand what else is out there and how it compares to what is out there.

I am able to use it. If I am able to use it, I would rate Microsoft Azure Synapse Analytics an eight out of ten.

It is useful for Azure services. I am using its latest version.

Its seamless integration with Azure services is most valuable. If somebody wants to use all Azure services, it is the best solution.

The ability to integrate with different Azure services from within the Synapse Analytics workspace is also valuable.

Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better.

I would like to see support for cross-DB queries.

I have been working with this solution for three years.

Its stability is an issue because they're still upgrading the Synapse Analytics workspace.

It is scalable to a certain limit. It is not as scalable as Snowflake, but it is scalable.

There are many available versions of Azure Synapse, such as Azure Synapse SQL Datawarehouse, Azure Synapse Analytics, and Azure Synapse Analytics workspace. You need to be aware of the features that you are looking for and accordingly choose the offering.

I would rate it a five out of 10.

I am using Microsoft Azure Synapse Analytics with Snowflake.

The solution has been working well overall.

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

Microsoft Azure Synapse Analytics is stable.

I have not needed to contact the support, everything seems to work.

The solution could improve by having better costing information.

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

My primary use case of this solution is as a data warehouse.

The most valuable feature of this solution is its filling of the gap between big data and classic data warehouses. As a solution, Synapse allows you to do almost everything. 

An area for improvement would be advanced analytics. The product also comes with a pretty steep learning curve, which could be improved. In the next release, I would like an improvement in internal security, which currently doesn't work at all.

I've been working with this solution for about two years.

Initially, the product had some issues with stability, but these seem to have improved with time.

Scalability is one of the main advantages of this solution.

Tech support is ok but more difficult tickets can take a long time to solve.

The setup was complicated because the data must be organized differently from the classic SQL database. There are also different techniques for query performance and managing caches, which makes the process more complicated.

Synapse is a very costly solution, and other products are available for less.

One of the main pros of Synapse is the ability to work with the classic data warehouse and the big data. Another is the ability to use the Spark engine for preparation. Before implementing this product, consider whether it will provide the results you want. If you are already using Microsoft products, Synapse is easy to integrate. I would score this solution as eight out of ten.