Microsoft Azure Synapse Analytics Reviews

The product is easy to use. 

One potential area for improvement could be the availability of an on-premises data lake implementation, as the product is currently only implemented in a cloud environment. 

Additionally, the possibility of integrating data from multiple sources could be beneficial. 

We have used Microsoft Azure Synapse Analytics for approximately three months.

The platform's scalability is similar to that of SQL databases. It requires developing components, implementing services, and performing other related tasks.

The initial setup process is straightforward. 

My advice would be to remain open to learning new things, particularly because working with Synapse Analytics requires a shift in mindset from traditional tools like SQL Management Studio to newer tools and approaches.

I rate it an eight out of ten. 

I work in the financial industry where the most important thing is PII so the solution's data masking feature is very useful for clients. 

The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge. A developer will feel at home using the solution. 

The product needs a tool that allows for work from a laptop instead of a browser. When working in on-premises environments, it is important to have all tools installed on a laptop rather than relying on internet connectivity which is a big inconvenience. For example, it would be brilliant to add an integration on Visual Studio to create all pipelines in an offline mode. 

The solution cannot store much data and might require purchasing additional storage. For example if you have 1 TB of data, processing it in the solution will cost ten times more than processing it in Databricks. 

I have been using the solution for seven months. 

The solution's stability is good. 

The solution is highly scalable. For example, if you have 100 DWUs, you can increase up to 20,000 DWUs by letting Microsoft know your requirements. Your needs for DWUs will be satisfied based on how much you are willing to pay.

Support wavers depending on the size of the customer. For example, a Fortune 500 customer will receive tremendous support and quick turnaround time. 

Smaller customers might find it challenging to receive support. 

The initial setup is very easy.

The solution is very expensive because it often requires the purchase of additional storage. Many customers are willing to pay for something that is available in the open source market. If the price of the solution isn't reduced, it will not sell well in the future. I rate the price an eight out of ten. 

Our company heavily promotes Databricks because of the solution's cost impact on our clients. Databricks provides a data lake and a warehouse framework that gives the same or better performance when compared to Synapse, but there is a massive learning curve to using it. Most customers are not aware of Databricks so they don't understand it or use it. 

Two negatives of Databricks are that it is cloud native with no option for an on-premises server and it does not have good integration with any of the IDs. I provided this feedback while I was in training and their team acknowledged the web browser is an issue to resolve. Most developers do not like to work in a browser environment because accidently hitting F5 will cause complete loss or the internet goes down and all changes are lost. These type of issues do not occur when working in offline mode. 

Six months ago, Databricks launched a new product called Databricks SQL that offers multiple platforms such as data engineering with or without a SQL server environment. There is a focus on targeting developers familiar with SQL because the product will only require a different kind of syntax but the SQL environment is still there. Databricks is investing heavily in training developers free of cost and providing certification seminars to increase knowledge of the product as it evolves. 

There are use cases for Azure Synapse with customers who do not want to move away from SQL Server or want a similar experience. The solution offers the ability to create an on-premises server with a SQL syntax that is familiar to developers with no learning curve. Most customers prefer Synapse until they realize the high cost and then they switch to Databricks. 

I rate the solution an eight out of ten. 

It's used for business case analysis and bandwidth utilization, etc. 

We are using its latest version.

It's feature-rich. It has a wide range of features. 

It's stable, but its stability could be better. However, we understand that it's in production, and new features are getting added and upgraded, so you do get hiccups sometimes.

I've been using this solution for more than four years.

It's quite stable. I'd rate it an eight out of ten in terms of stability. There are very few outages or errors during the configuration.

It's scalable. I'd rate it an eight out of ten in terms of scalability. Our clients are enterprises. 

I haven't contacted them, but it should be fairly good. I haven't had many issues with it.

I'd rate it a nine out of ten in terms of the setup. It has a GUI, which is awesome. Its deployment duration varies based on the case to case. We have quite a few SMEs for deployment. 

It doesn't require many people for maintenance.

It has been good so far. I'd recommend it to others. I'd rate it an eight out of ten.

I mainly use Synapse Analytics to gather data, do aggregations, and generate reports.

Synapse Analytics' best features are notebooks, pipelines, and monitoring.

An improvement to Azure Synapse would be more templates for specific domains. 

I've been using Synapse Analytics for four months.

Synapse Analytics is generally stable, but its performance can be slow when performing very large datasets.

Synapse Analytics is definitely scalable.

Microsoft's technical support is fast and responsive.

Previously, we used Databricks.

The initial setup was straightforward, and I would rate the experience as 4.5 out of 5.

We're getting a good ROI from Synapse Analytics.

I understand that Synapse Analytics' pricing is lower than Informatica's.

I also evaluated Informatica Cloud Integrations but felt that Synapse was more straightforward.

I would give Synapse Analytics a rating of nine out of ten.

The stability of the solution is pretty good. It's one of the solution's most valuable aspects.

The useability, the user interface, is very user-friendly.

The solution needs to improve its integration capabilities. It needs better integration with SQL and other databases. 

The initial setup is complex.

The product needs to implement more machine learning and artificial intelligence.

If they had more IoT and streaming capabilities, it would be helpful.

The product could use more analytics tools.

It would be helpful if we could use the product with less coding.

Normally, the solution is quite stable. The performance is pretty good. We don't regularly deal with issues. It doesn't crash or freeze, and I can't recall any bugs or glitches.

The solution can scale, however, it is expensive to do so. If a company wants to expand, it will have to pay. Therefore, they should be prepared for that.

Currently, we have about 200 people using the solution.

I don't have a direct relationship with the technical support when I have a problem. They aren't very good. We aren't satisfied with the level of support we get.

The initial setup is not too straightforward. It's rather complex. We had to get some outside assistance.

The deployment process took us about three months. It was a while.

We hired a consultant to help us with the implementation of the solution.

I don't have exact KPIs on this, however, I need to improve the sizing in order to improve our ROI.

The is a monthly licensing fee. I can't speak to how much we actually pay, however.

There is just one fee. You do not have any more costs over and above that.

While we didn't previously evaluate other options, in 2021, we need to explore the other solutions. I intend to look at the Amazon and Google Cloud platforms as other options.

We are both partners and end-users of the product. We use it internally and we use it with some of our clients.

I would caution new users that there is one parameter they need to watch carefully. That is the size of the data warehouse. If you don't configure this parameter to be as small as possible, your costs will be quite high.

I would rate the solution at a seven out of ten. It's a stable platform, however, the price model is questionable in comparison to Amazon and Google and the contact with support is a problem for me. 

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.

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 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.