Microsoft Azure Synapse Analytics Reviews

I work with Azure Synapse Analytics, Power BI, and Premier as a data administrator, using Microsoft's Azure cloud infrastructure. Azure Synapse Analytics is the principal data administration tool for our internal data warehousing, but we also use it for our customers' data warehousing and analytics in different industries. For data entry, we use Microsoft Power BI.

Internally, we have about 200 personnel currently using Azure Synapse Analytics, including data specialists, service managers, and other tech workers. It is not extensively used by all, however, because we don't often use it for very large amounts of data, except where financial data is involved.

Azure Synapse Analytics helps us move quickly when it comes to finding data warehousing and analytics solutions for our customers.

We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for different sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on.

It is our main data warehouse solution, and the one big feature I appreciate is all its various analytics functions. The built-in analytics also makes it an attractive option for our customers, where we act as a service provider for them.

Unfortunately, we have had some issues with the dashboard reporting. Sometimes, the data for specific periods would just appear blank on the dashboard. To investigate this, we worked with a Microsoft incident agent and it turned out to be a result of bugs in the platform when dealing with specific types of queries in Azure Data Factory.

We have also encountered some bugs regarding incompatibility with certain versions of Power BI. In the past, Power BI used to integrate nicely with Azure Analysis Services which we used as a bridge between Power BI and Synapse Analytics, but they have since discontinued the features that worked so well for us.

Apart from fixing bugs, I would also suggest:

• The learning features and documentation could be improved and expanded on.
• The calculation and forecasting tools could be made more clear and easy to use.
• The price could be lower.
  

I have been using Microsoft Azure Synapse Analytics for one and a half years now. 

When it comes to stability, Synapse Analytics has suited us well, because it's very fast, i.e. it has good performance. Compared with the on-premises SQL solutions we've used, the results are two times as fast.

There are some bugs that we've encountered with the platform but we are able to work with Microsoft directly to resolve them as they come up.

I'm very impressed by the scalability of Synapse Analytics, even though we don't use it for huge amounts of data most of the time. Combined with the availability of machine learning and other features in the cloud, it has a lot of potential, especially in the area of finance.

In our context as service provider, normally we have direct contact with the server. But in some cases, we have needed extra support which was very slow.

For technical issues, I often solve them myself using Microsoft's learning resources and support forum.

For me, it's the fifth data warehouse I've used. Other specialists here also use other warehousing solutions based on SQL but for the moment Synapse Analytics is the best overall solution for us primarily because of its ease of implementation and flexibility.

Because I was not familiar with the solution beforehand, the initial setup was quite complex. I had to learn a lot in the beginning stages. I'm grateful that there is help to be found in the Microsoft forums, however, and there are also options to study for certifications that help you learn how to use the platform properly.

It took approximately six months to implement Azure Synapse Analytics in our organization. We set up the data warehouse features for internal use across 200 users, including data specialists, service managers, and tech workers who manage our own data and also our customers' data.

For the main deployment, we used a third-party support provider in Chile who helped us greatly.

We normally pay between $300 and $500 per month, which is quite expensive for how much we actually use it, performance- and usage-wise. They have a cheap version and an expensive version, and our usage usually falls in the middle ground, which makes it not as cost-effective as it could be.

We evaluated on-premises SQL solutions for data warehousing, but our main motivation for using Synapse Analytics instead is that it lets us come up with and manage customer solutions very quickly. Some specialists are still using other SQL solutions as well, however.

There is always room for improvement with Azure Synapse Analytics, but for our use cases it works very well. 

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

We are an IT service provider. We develop solutions for our clients and this solution is used in some aspects of that.

The dashboards are good.

We haven't had any issues when it comes to customization.

The security seems to be okay. It hasn't given us any problems and we don't feel insecure.

The pricing seems to be quite fair.

I know their roadmap, and I am looking forward to what they have already published.

We've been happy with the level of reporting and documentation on offer.

There aren't any features that are really lacking in the solution. We don't really have any issues with it in its current form.

When we used the on-premises deployment model, we had data latency issues and suffered from page performance problems. However, since we've moved to the cloud, we haven't had these problems.

The initial setup has a bit of a learning curve.

We've been using the solution for the past 18 months so far.

The solution seems to be scalable. We haven't had any issues with bugs or glitches. It doesn't crash or freeze. It's quite good.

The scalability has been pretty good, in our experience. We have been able to scale it twice to the number of users we needed. We were also able to double the amount of data load. We haven't had issues. If a company needs to expand, it should be able to do so without problems.

We've dealt with technical support and have found them to be quite responsive and knowledgeable. We're quite satisfied with the level of support we have been getting so far. They're helpful.

It's hard to gauge the difficulty or simplicity of the setup. For our company, we were learning the processes as we were doing it. In that sense, it was challenging due to the fact that we had to learn and then do. After a period of time, we were able to get comfortable.

We handled the implementation ourselves. We taught ourselves about the process as we went.

We pay a licensing fee on a monthly basis. We find the pricing to be fair among the competition.

We're just end-users and customers. We don't have a business relationship with the organization.

We're using the latest version of the solution right now.

I'd recommend the solution to other organizations.

I'd rate the solution at a nine 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.

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.

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.

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.