Microsoft Azure Synapse Analytics Reviews

Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across. 

I have been using Microsoft Azure SQL Data Warehouse for three years. 

It could be more stable. 

It is a Cloud platform and so it is easy to scale.

When it comes to first level support, most of the time it's not a technical issue, it's a configuration issue where data mismatches. I get support anytime I want. Within an hour I can get anybody on the call and get the issue resolved. They have a one-to-one support channel which we can email when we require assistance.

We installed Datawarehouse in a couple of minutes. However, the configuration based on our data models took time. It can take us weeks because that's where our optimization sits. Just tuning the parameters can take several days' at a time. 

The price of the package is not expensive and depends on how much it is used.

I would rate Microsoft Azure SQL Data Warehouse a nine out of ten. 

I used it for a project thesis for my school project.

I like its performance. It is well-structured and offers a lot of practical options. Because of the visual design of the product, it is very easy to find icons and other visual elements.

It took me more than two weeks to understand how it works. I had an intensive training session to understand it, which was enough. It was not hard to understand how it works.

I am a researcher. For people to be able to research a solution, there should be at least a free trial. Just advertising a product or saying that this product is better doesn't work. I would strongly recommend providing a lot of free trials and trainings. This will also help Microsoft in having more users or customers. Oracle provides some free trials. You can just go for a free trial and use your database online, which is very good.

I have been using Microsoft Azure SQL Data Warehouse for three months.

It was ready when I started to use it. I just had to do my project.

Its price could be better. It was a school project, and I got it for free. If I try to pay through my company, it is a little bit more expensive as compared to Oracle.

I am also using an Oracle solution. Oracle has been in the database field for a longer time, and it provides you more familiar terms that the users understand. When users start to work with an Oracle solution, they are more familiar with the terms. They just need basic training to understand it, but with Microsoft Azure SQL Data Warehouse, they have to be a little bit more experienced. In order to understand this product better, they have to know how other Microsoft products work.

It is a powerful asset if we can use it and learn more about it. If Microsoft can give some free training sessions for students and amateurs, it would be helpful in knowing more about this product from inside. 

I would rate Microsoft Azure SQL Data Warehouse 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.

There are around 10 people using this solution within our organization and we have plans to increase the usage. 

Microsoft Azure uses the Massively Parallel Processing concept for data warehousing. The speed is great and the architecture is excellent. 

Microsoft should develop an interface to make it easier to shift from on-premise to the cloud.

There needs to be a lift and shift tool to move on-premise, IMS high-volume data to synopsis sequence data on the cloud.

I have been using this solution for two years.

The stability is okay, but it could be improved. I believe Microsoft is working on fixing this at the moment.

We are satisfied with the technical support.

We used to use an AWF product, but Microsoft Azure is a better cloud-based solution compared to AWF.

Our license is very expensive.

I would recommend this solution to other enterprises.

On a scale from one to ten, I would give this solution a rating of seven.

The primary use case is for the fast retrieval of data, which is in the data warehouse on-premises and migrating it to the cloud.

The most valuable feature is performance gains.

The scalable nature of the data warehouse on the cloud, and the flexibility that you get, and important features.

I would like to see them provide the ingestion of images.

I have been using this solution for more than three years.

It's a production that keeps changing and we are always using the latest version.

This solution is quite stable. It's in the cloud and we have not faced any issues.

This solution is scalable.

Technical support was not needed because of all of the documentation available.

The initial setup is straightforward.

All of the prices are available online.

My advice would be to move your on-premises data warehouse to the cloud. Move it there faster, as you can get more performance gains and it's also a robust infrastructure.

I would rate this solution an eight 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.

We are developing our SQL Data Warehouse locally, using SQL Server 2016 on our private cloud, and we will be migrating it to Azure once it is ready.

The company for which I am working deals with products in the leisure industry, such as museums and swimming pools. They use the data warehouse solution for big data reporting. Currently, we are developing a multi-platform data warehouse that can support the reporting requirements for all of the customers. Whatever analytics they want to perform will be done with the data warehouse, and not the SQL database application.

My role is to design the data warehouse, and once that is complete, we need to build the data pipelines so that the data can be moved from the application databases into the warehouse. Then we will design the OLAP servers and OLAP cubes, vertically, to give us a presentation layer on top of the data warehouse. This layer is what the customers will be using.

The most valuable feature is the incremental load because we do not need to refresh the entire data on a daily basis. We have a nightly load where all of the data is updated, and it is a very good feature.

The transaction log shipping gives us the ability to replicate the database onto different servers for backup and synchronization.

The major concern is that I have a hard time with having to version control the data warehouse all the time. As it is now, I have to open all of the ports and push everything onto the server. I would like to see version control implemented into the data warehouse. This would make the tool perfect. 

I have been using this Microsoft Azure SQL Data Warehouse for about two and a half years.

The version that we have been using, 2016, is stable. We have not used the 2019 version in production yet, but there is a team that is evaluating that version right now. I'm not sure of the reason for it not being in production, whether it is related to stability or not.

The scalability is good. I think we are already using a high availability cluster for 2016, so I assume that it will be the same with the 2019 version. We are also using it with our data recovery system, so it is not an issue.

We have approximately twelve to fifteen developers and approx. 900+ customers who will be using the data warehouse. We are acquiring customers on a monthly or quarterly basis, so it is a pretty big user base and we expect that our usage will continue to increase.

We don't have too many technical issues, so overall, I think that it's good enough.

I began with Microsoft SQL Server and have been on the Microsoft platform ever since.

The initial setup is pretty straightforward. It has been a long time since we first implemented this solution, but since that point, we have created a custom handbook that we can follow in order to set it up.

There are certain design concepts that can be used to design a data warehouse. My advice to anybody who is implementing this solution is to first study the user's needs, and then go with that approach. The design will be specific to the needs.

I would rate this solution an eight out of ten.