Microsoft Azure Synapse Analytics Reviews

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.

Our general use case is for government purposes, and therefore, I really can't get into too much detail about it.

The solution is great at saving time. Overall, we spend far less time putting together static reports than we used to.

We're able to generate some dynamic reports. I find that very valuable to be able to see our data in such unique ways.

The pricing is pretty good.

The product is very user friendly.

After only using the solution for three months, we haven't yet really gotten into every corner of its capabilities. It's hard to say what might be missing in terms of features.

It would be ideal if the solution could be better used intuitively by the staff without having a great deal of training. An organization should be able to adopt and operationalize it throughout their company with minimal training.

I've been using the solution for three months at this point. It hasn't been too long.

The solution is quite reliable. We haven't experienced any problems with crashing or freezing and haven't really had experience with bugs or glitches. It's stable.

The solution is scalable. A company shouldn't have issues expanding it out.

In our organizations, we have less than a dozen users, and those are mostly IT and IT management people.

Technical support is okay. I'd rate them seven out of ten. We're satisfied with the level of support we are given.

We were searching for a solution. When we found it, we found something we could use, and then we just stuck with that. We didn't have a previous solution. We had nothing before.

The initial setup is not complex at all. It's pretty straightforward. I'm not that technical, and I was able to handle it.

We've found the pricing to be fair. It's not too expensive.

I'd recommend the solution to other organizations. If they have time, I would suggest a company spends more effort looking at some different offerings. That said, generally, if you don't have a whole lot of money to do something, it's a decent option.

We haven't used the solution for too long, however, it's offered us everything we need in terms of features and capabilities. On a scale from one to ten, I'd rate it at an eight.

I am a consultant, and when I go on-site, it's to determine how they can move to the cloud. Often, clients want to migrate because everyone else is. Others want to because they assume that they are going to save money. They will require less support staff in-house and they won't have to purchase servers.

Customers have a need to cut back on expenses, and equipment. Their servers are becoming obsolete and are required to update their licensing. Rather than doing that and creating a larger overhead, they look into Microsoft Azure. It might be a better way to go and it's less money upfront. 

Some clients have already implemented VMs. A lot of their data is stored that way. There is a difference when you move that to the cloud. 

If you share it back and forth, you have your hybrid where you have it in the cloud and on-premises. It depends on the company and what their plans are.

There is an automated tool that you can analyze your data sources and identify whether or not you can upgrade them and you can also use it for SharePoint. I've used Azure for that purpose.

In regards to data warehouses, I'm doing the upgrades from on-prem to in the cloud, or a combination of both.

With our current COVID situation and being under lockdown, many of the businesses are moving to the cloud and it's been beneficial for us.

Many consulting agencies have set up online businesses where you can reach out and they will do webinars to introduce you to things. I have been involved with that too and it gives customers a taste of things that will give you more of an opportunity to sell it to them.

What I use the most is the tool to identify the upgrades. When you have a data warehouse on-premise you have jobs that run. Similar to an SQL agent, you are not comparing apples to apples, there are differences between the way the jobs are run on Azure versus the on-premises.

We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud.

They can be leary of moving to the cloud, They want to determine when someone has access to the client's data when sharing, and are in the same environment, that the data is secure. Essentially, they are accountable and need to be able to identify how secure their data is for their clients.

Technical support needs to improve.

Microsoft improves all of the time, but there are some things where different vendors offer data warehousing and data governance that you can build and workaround. It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft.

I have been working with Microsoft Azure SQL Data Warehouse since 2012.

It's in the cloud and updated every six months.

The stability is good.

It's a scalable solution.

Our client's companies vary in size. They are across the board from insurance companies, healthcare, marketing, and manufacturing.

Early on, Microsoft was not good at supporting its product and issues. I had lost a contract because showed up to late to resolve an issue that I was having when doing a comparison between Microsoft and an IBM product, where I wasn't able to transfer the data fast enough.

I have reached out to the technical support team since and some of it is really good, whereas, at other times, you are better to post it online and try to resolve it yourself. They support the tool but don't have to experience with the tool.

I would rate the technical support an eight out of ten.

I have used Oracle as a backend, but I am not skilled with Oracle. The frontend has always been with Microsoft.

You couldn't be a novice really and follow it.

As long as you were using the tools already, it's pretty straightforward. 

They do have resources you can contact.

You could have one or two of your team join the Microsoft groups and learn more that way as well. 

There is a lot of planning and setting the right people in motion to work with it.

There is a cost calculator available online that allows you to input your entire scenario, and it will get back to you with information on what the costs are going to be. You can adjust it to include different requirements to best suit your budgeting needs.

Microsoft also offers suggestions on what you would need based on your account.

Microsoft is trying to be more competitive and wants to be very accommodating.

Clients will look at Pro Dell Compare. They use the tool to determine how simple it is or how complicated it will be to move their data. They consider whether they need to make use of one of Microsoft's partners to have them help, or can they do it themselves, and they determine how risky it is along with how simple it will be. Will they have enough manpower, and whether or not they're going to have to hire external consultants to help them. They also consider whether they are going to move their applications or are they going to wait? and what's going to come first. They create a plan.

You want your onsite team to look at, our use cases, look at what we're getting back for information, and then problem-solve. Think about any additional questions, and is this really feasible, because it's not free. You can start out using it for free for a short amount of time.

Microsoft is improving and as they grow, I see that they are pushing towards the enterprise. If you don't quite fit, then you are pushed into it whether you are ready or not.

You really have to consider where you want to be and what you are currently doing.

Anyone looking to use Microsoft Azure SQL Data Warehouse, I would advise them to do the research, hire an architect, screen them well, and know their background to ensure that they are going to provide a service for you. Have them work alongside the project manager to identify the resources and what needs to take place and build a plan.

I would rate this solution a nine out of ten.

We primarily use the solution for analytic purposes. It allows us to store data for years and then go back and look up information to learn things like how users function, react, follow trends, etc. It allows us to follow past and recent demands for products as well so that we might be able to find the reasoning behind the action or trend.

With this solution, I can better understand buying patterns and user habits. I can tell in real-time a customer's review and purchase based on that. I can tell that from the cloud data of Azure Data Warehouse.

The solution offers a variety of different features.

There are two layers, so data storage and computation are separated.

For the customer, there aren't any storage limitations, so you are able to explore and size of data including megabytes and terabytes. Once you have stored the data you can analyze the data that if you have in order to write some complex queries. After that, the solution makes it possible to visualize that data itself. 

The computation makes it so that you can run scenarios without an impact on your storage location.

If you compare the product to other solutions, you'll notice it takes less time for less cost. All other vendors have different architecture so their pricing is a little bit different and they are charging pricing per second. Microsoft charges per unit, or DTU, Data Transfer Unit. It will charge based on how much data you are consuming and how much data you are doing transactions with. It is monthly not daily.

Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task.

The solution is consistently improving a lot of things, including security features. There are eight or nine different security features there. You can even encrypt your data.

There are features coming int he next few quarters that will be helpful. Soon, Power BI will be directly integrated into Azure. We need to have some Spark tools also available so we can directly select customers and don't need to install everything.

There will be features added that relate to application development. There's hopefully going to be more flexibility with the XML. Right now, for example, Data Warehouse is not able to give XML files and your file put is not correct. The feature will hopefully allow us to read XML.

The performance needs to improve in future releases.

We're hoping that Microsoft will add integration with the Amazon AWS platform.

I've been using the solution for four years.

The solution is quite stable. We haven't had any issues with it in terms of experiencing bugs and glitches.

Microsoft has different sizing options that comes at different price points. It's easy to scale up or down. If you find, after a few years, your needs are growing, you can increase your BTU size the maximum may be about 13,000. 

With this solution, we can actually automate scalability, which makes it very easy to scale. If you require more data, it will automatically increase your DP size and process the data. We have the flexibility we need so that, whenever a node gets filled, we never have to worry. Another node will pick up and process the data.

With Snowflake, in comparison, if your system is not running, then Snowflake will go into an auto suspend mode. You can sync the time, and, within the 10 minutes, if the system is not running, it will go to an automatic suspended mode. There is no charge in this mode. In that case, we have to manually find what we need to virtualize the function. 

Azure has other mechanisms in place. We can write Azure functions and we can schedule the Azure functions in order to automate them. We can do similar kinds of functionality, however, we have some additional coding we require for Snowflake. 

We've had no need for support. Everything is automated and pretty much taken care of. We need to configure everything and the Azure portal will get us to the dashboard. In that dashboard, you'll get all of your current information including information on how the system and the cluster is running. 

The backend is very nice. There are a lot of additional features that help you manage the product. As users, you will get the visualization dashboard. It is very easy to see, which nodes are running and how much data is processed. We can see everything on the portal, and that makes everything very easy to handle.

I've had prior data warehouse experience with traditional systems like the Oracle, Superserver, or Teradata.

Snowflake is the only provider with no cloud platform. You have to buy a platform in order to adopt it. Microsoft Azure, AWS, and Google Cloud all have their own dedicated platform. They have their own dedicated data centers.

The initial setup is not difficult. If you have access to the subscription you can start using Azure Data Warehouse and being to create the services. There are security features also. You can give someone full access, and you can set access for others too. Developers will need access so that they can develop it out. It's a pretty straightforward process.

In comparison, I find that AWS is much more costly.

We're a Microsoft partner.

I have experience with the Microsoft Cloud Data Warehouse specifically within the Unix cloud environment.

We're using the latest version of the solution.

It's important for organizations considering the solution to consider their business requirements and expectations. They need to be clear about what type of cloud solution they are looking for. We help our clients do this and interview them to find out what their needs are so that the best platform can be chosen for them. It may be Azure. It may be Snowflake. It depends on the company's needs.

At the end of the day, the customer will always want the best possible pricing. They'll typically ask how they can save money but have high throughput or more input with less price. If that's the case, Microsoft may be the perfect solution.

I'd rate the solution 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.