Microsoft Azure Synapse Analytics Reviews

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.

We're using this solution for analytics and its modeling capabilities. It allows you to have your visualization on top of your synapse analytics. We are partners with Microsoft. 

I like that the overall deployment and integration is pretty fast and then you also have virtualization to Power BI so it's also quite cost-effective.

For improvement, I would like to see more connectors and better integration for Hadoop. There are currently limitations for Hadoop on-prem. I'd like to see better integration and more flexibility. 

I've been using this product for almost a year. 

This is a stable solution. We have four companies who are customers of this solution and we have a team that deals with any problems. 

The product is scalable. 

The technical support is very good. 

The initial setup is straightforward and takes around two hours. 

There is a license for Azure, and whether it's a monthly or annual payment depends on the agreement you have with Microsoft. A long-term plan is more cost effective. 

I rate this solution a nine out of 10. 

We mostly provide cloud data warehousing platforms for major banks in Canada. What we're trying to do is to create a standard platform environment that is compliant with the regulatory requirements imposed by the government and financial overseeing institutions for the banks. We help them to onboard the lines of business to these platforms and migrate the existing workloads to the cloud platforms.

The ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage.

The major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse.

There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process.

When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

I have been using this solution for two years.

Generally, it is stable. We all heard about the Active Directory issue earlier this week, but it was not related to Synapse. It was related to the Azure platform.

Its scalability is good. The only thing is that when you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

We're working with banks, and they have great support because Microsoft has multiple representatives closely monitoring each account. Whenever there is an issue, they're being proactive. They're making a lot of money out of it. Most of the banks, on average, spend between 30 to 50 million a year on Azure. They're pretty large accounts, and Microsoft has dedicated people supporting everything related to Azure.

We deliver platforms to different banks. Some of the banks go with Synapse, and some of the banks go with Snowflake. Overall, these are two major alternatives available right now.

There are multiple differences in terms of the support of different workloads. When one of the banks made a decision to go with Snowflake, the major reason for it was the support for the multi-cloud environment. The major pro of Synapse is the service, and the major con is that when you decide to move out of Synapse, you would have to rewrite the entire thing, whereas, with Snowflake, it would be just simple migration to different cloud providers.

It is relatively straightforward as long as you understand what you're doing.

You don't really need to maintain it. That's the entire point of the cloud. You pay for it to be maintained. 

We do deal with monitoring and other similar things, but most of the activities are automated. Overall, it doesn't require a lot of labor around it. We're delivering the platform as infrastructure as a cloud, so everything is going through the pipeline. 

It goes by the usage, and there are some limits. Synapse goes by particular pricing, and it is expensive. Both Azure Synapse Analytics and Snowflake are pretty expensive. They don't have standard pricing. They deal with each customer differently.

For working with Synapse, you need to have an understanding and knowledge of the product to take full advantage of it. Synapse has a lot of features in terms of scalability, such as resource management, distribution, and partitioning. There are a lot of things that you need to consider when you go for it. It is not a simple database that you put in there, and it is running itself. 

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

It is for business intelligence. We are gathering all the data from legacy systems and transforming the data. We are then pushing the data back towards Power BI.

The whole solution is interesting for us.

They should provide a less expensive version with a smaller setup for small businesses. Currently, its price is quite high for entry-level or small businesses. In terms of integration, new connectors are always welcomed.

I have been using this solution for a year.

It is quite stable.

We don't scale up because the current level is enough for our customers. Our customers are small and medium companies in Europe.

I don't use their support.

It is complex. There are too many products that we need to involve in its setup, such as data factory and machine learning, and they're integrated so intricately. You need to have quite good skills to work with this. You would need a partner. You cannot do it yourself. The deployment usually takes a month.

It requires a less expensive version because currently, not every customer is able to buy it. If it could have a smaller setup that doesn't require so many resources, it would be helpful, and we would be able to use it in more cases. We are a small country, and most of our customers are quite small businesses.

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

The solution's scalability is very, very good. It's one of the most important aspects for us. 

We really need our data to stay in Western Europe. As an insurance company, it's important for our business. Microsoft can guarantee that it stays in Western Europe. That way, data is not processed anywhere else.

It's widely acknowledged as an excellent product throughout the industry. There's a lot of knowledge about it in the Netherlands as well. It makes it very easy to find a consultancy and also employees who can help us with its modern architecture.

The initial setup is easy. You don't need extensive training. It's an intuitive process.

What I would like to see is a possibility for time travel on the data. For instance, a financial department would like to do an analysis of the data set as it was for the first of the month while another department wants to run the analysis about how things went yesterday or last week. They have different starting points for the queries. I've seen Snowflake handle tasks such as these. It's got a feature called time shuffling, which can show me what's there on a certain variety of dates. It's very convenient.

It would be great if we could query the data of the day as well as in the data warehouse. 

They should have scalable memory processor options for the data warehouse.

While the solution is flexible, sometimes this works against the user.

We're new to the solution. We started using it last year around April or May. It's been less than 12 months so far.

The solution is scalable. It's online. That means you can scale it online and can stop the database to change the scaling of it.

We've had a few calls with technical support. They were very helpful and responsive. We have been satisfied with their level of support.

The initial setup is very straightforward. It's not overly complex. A company shouldn't have any issues with the initial setup or implementation. You don't need deep technical insights to have training.

You can create a floor space in an hour. That's no problem. Afterward, you have to work with the data and do a few more things in terms of configuration, however, it's not hard.

We are using the latest version of the solution.

I would rate the solution at an eight out of ten.

I would recommend Synapse, however, it depends on which industry an organization is working in. It can be complex, and often, you have to choose between several tools. They're all able to do the same job, they're just more industry-specific in some cases. 

If you want to transform your data, you can choose between the database, data factory, and SQL, and even other tools.

This means it is very flexible, however, it also makes it difficult to administer. It's not that one of these sources is harder per se. It's more about what is the best for the job. Sometimes you create something and it doesn't perform and you have to start from scratch.