Microsoft Azure Synapse Analytics Reviews

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.

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 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.

We are a software development company and this is one of the solutions that we recommend to our clients. The applications that we develop make use of this technology.

Using Azure SQL Data Warehouse means that you don't have to worry about big servers.

The best part is the easy and user-friendly administration and handling of the data.

The configuration for things like high-availability could be more user-friendly for non-technical users.

We have been using Azure SQL Data Warehouse for almost twelve years.

This is a stable solution with no issues.

Scalability is the best part of going with a cloud-based solution. I don't have to worry about server space. Azure elasticity allows us to scale as much as we want, and it is pay-as-you-go, so we can scale up as we need to. What we propose to the people who are implementing this solution is to start with the minimum requirements and then scale up based on demand.

We have not seen any problems with technical support. We have Microsoft certification, so we very rarely contact them for any help. Normally, we handle the support for our clients.

The initial setup is straightforward. The requirements are very clear, and there is not much of a problem when you're doing it.

One of the recent upgrades we have done that included high-availability, loading the data, and setting everything up, took about a month and a half.

The licensing fees for this solution are on a pay-per-use basis, and not very expensive.

The core strength of Microsoft technologies is ease of use and administration, regardless of the type of product.

This is a good solution to go with, the cost is reasonable, and I recommend it.

I would rate this solution an eight out of ten.

We haven't really implemented any SSIS. I haven't been in a project where it was implemented as part of the data we have been building.

The features we've found most valuable for data warehouses is extracting data, SSIS packages, and the DBs.

So far, with the current SQL that I'm using compared to what we've previously used, I'm happy with it. I wouldn't necessarily point out anything that needs improvement.

From my point of view from what we have implemented recently, I'm happy with the solution, I'm happy with the performance. I'm not entirely happy with the billing model. I'm not entirely happy with how the enterprise services are pretty expensive, but that's about it.

I have been using this solution for around 18 months.

It is very stable.

I think the architectural design is very scalable.

I never contacted Microsoft customer support. 

We do have access to it, but we haven't needed to.

I've used Tableau, I've used SQL DB, I've used SAP DB.

The initial setup wasn't complex. It was okay. It wasn't complex at all.

To set it up within full compliance with our cloud infrastructure team, I'd say maybe two weeks after beginning our testing. I'd say the team wasn't a hundred percent devoted to setting it up as they had other things to do. So I'd say I'll give it two weeks to be realistic for a large organization.

It depends on whether you have those resources internally or not. If you have internal resources you wouldn't need to outsource, if you don't have, you would. So it's not a matter of how good that application is but a question of whether you have the capability in house.

The enterprise services are pretty expensive.

We are a solution provider and we provide different tools for our clients. Microsoft Azure SQL Data Warehouse is one of the solutions that we have implemented.

The use cases vary depending on the client. We have a couple of clients who are moving their data from on-premises to Azure databases, and they are using this solution primarily for reporting analytics. They also use visualization tools on top of the reporting.

The main advantage of using this solution is its ability to scale and handle very large amounts of data, in the petabyte range.

When we are not using this solution we can simply shut it down saving us costs, which is a nice advantage.

With respect to what needs to be improved, concurrent connectivity has some limitations. 

We have been using Microsoft Azure SQL Data Warehouse for about one year.

This solution is stable.

We are satisfied with the scalability.

A lot of people use the analytics and I would estimate it to be between 50 and 100 users. Most of them are business users, although some are power users who built the system for them.

It is good technical support in general, we find. We were in contact with them when we were doing a migration from on-premises to the cloud, and it was very nice.

The initial setup is straightforward.

This solution is being changed from day-to-day. Now it has become Synapse Analytics and a lot of things are being added to it. I'm curious to see how that turns out. They have a lot of new integrations and features, including predictive analysis and big data integration. They may have solved the issues with concurrent connectivity, so I'm curious to put my hands on it.

The product is being upgraded and updated to support a lot of analytic features, and it is a great tool to use.

I would rate this solution a nine out of ten.