Microsoft Azure Synapse Analytics Reviews

I use Synapse Analytics to process data for transformation, create external tables, restrict user access, and for reporting.

Synapse Analytics' best feature is its ability to process large files.

Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node. In addition, the integration with other solutions like Power BI and Azure SQL Database is very slow and leaves a lot to be desired. In the next release, I would like to see a feature to offload Synapse files directly into Gen2.

I've been working with Synapse Analytics for about a year.

Synapse Analytics is fairly stable.

I haven't seen any issues with scalability. 

Microsoft's technical support fails to give us solutions and leaves us to figure out the issue for ourselves.

The initial setup was straightforward.

I also evaluated Redshift from Amazon, which is much more stable than Synapse Analytics but takes a lot of effort to convert into ORC and load.

I'd give Synapse Analytics a rating of seven out of ten.

We use the solution for integration to enable the data to reuse it in the power gap.

I like the simplicity of the integration of the data and the variety of the language you can use to integrate that.

It offers a straightforward setup.

The solution can scale.

Its stability is good.

There are some limitations. The filing can be improved. Some improvement in the filing is necessary. It needs some kind of growth in the filing development in order to reuse some activities.

I'm pretty new in the company. I started in January. However, they have been using this tool for two years.

The stability is great. There aren’t bugs or glitches and it doesn’t crash or freeze. It’s reliable.

The solution is scalable.

We have about 20 people using the solution in our company.

I haven't had any contact with technical yet, so I cannot evaluate their level of service.

The solution is easy to set up initially.

I’m not sure how much the solution costs.

We buy direct from Microsoft. Our company may be partners with them.

As Microsoft Azure Cloud, it only has one version. I don't know if there is a version number. 

I would advise users to start loading the data beforehand and understand very well how the tool works and how it's useful. That way, you can evaluate the best solution. Sometimes you need to start to load data and review all the alternatives in the solution.

I’d rate the solution a nine 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 use case depends on different things. For example, for banking, it would be risk management, fraud, and anti-money laundering. For retail, it would be an omnichannel customer experience. For sales, it could be upsell, cross-sell, retention. It's different for every industry.

The solution is like a marketplace in that it's easy to consume. 

It's scalable; you can scale up and scale down.

The standard things that you see from any cloud perspective make it very attractive.

It is easy to set up.

We'd, of course, always like to pay less for the service if we can.

I've been using the solution for a few years. 

The solution is stable. There are no bugs or glitches and it doesn't crash or freeze. It's reliable. 

I work for Accenture, so there are hundreds and thousands of customers on Microsoft.

The solution scales very well. You can scale up or down as required. It's very easy.

I don't really interact with technical support, so I can't really comment on their level of service.

I don't think it's very complex to implement. We have our own expertise. We have our own IPs to set it up and therefore it's not really complex. It takes a week to ten days to have everything up and running. 

Typically, a pool of six or seven people should be good enough in terms of handling deployment and maintenance. Usually, it's comprised of a mix of managers, admins, engineers, and/or developers.

Maybe it takes over a period of two or three years to see an ROI of maybe 50% to 70%. 

I don't deal with the licensing aspect of the solution. 

I'd recommend this solution to other users. 

I'd rate the solution eight out of ten.

 I'm a senior consultant.

For those working in the retail sector, this product can capture all the transactional data throughout a company's stores, process them, and put them into the Azure Synapses. Once you have the data, you can clean and aggregate it. On top of that, it has a reporting tool so you can connect to those Data Warehouse Synapses and pull up your reports which can then be used to prepare the dashboards and enable more insight.

Non-structured data is unavailable with this product. 

The solution is stable. 

Azure Synapse is serverless architecture, so you can scale as and when required. It makes no difference if there are 100 users or 1,000 users. We have around 50,000 end users.

The customer support is generally quite good. They follow up relatively quickly although it can sometimes take more time if it requires an SOP to follow up. 

The initial setup is straightforward. It's a matter of connecting to your visual studio or management studio.

It's important to understand your business needs and choose an appropriate solution based on the industry you work in and what needs to be achieved. There are a lot of tools available on the market, it's important to get the right one. 

I rate this solution eight out of 10.

We are using Microsoft Azure Synapse Analytics to find some evidence or outlier in our analysis about the application of the public health service and public money in the sector in Brazil. We are a public institution that is responsible for auditing other public institutions. We use these kinds of tools to find some evidence and outliers to audit with a little bit more documents or evidence.

The most valuable features of Microsoft Azure Synapse Analytics are the user experience because it is easy to make analyses, load different databases, and different resources. Our end users can do the analysis by themselves without IT supervising. This is a great aspect of the solution, it's better for our environment.

The interface of the solution is good.

Microsoft Azure Synapse Analytics can improve by increasing the size of the files that we can load on the platform. We have some files that are too large to be loaded and it would be a benefit to us if the limit was increased. Additionally, the way we use the tool for generating reports can be made better. They should add some drag-and-drop rules without the need of programming these rules using some programming language. It would be helpful if we did not need someone that was technically advanced to be able to do it with, such as someone with no IT background. Having a reporting tool without code would be great.

I have been using Microsoft Azure Synapse Analytics for approximately six years.

We use this solution as a data warehouse. Power BI allows us to visualize the data while analyzing data from the data lake through Serverless. We have not used too much of the pipelines within the Data Factory because we have an isolated Data Factory for that.

This is a stable solution with many functionalities.

The only issue that we have run into with the solution's performance is with regard to concurrency.

We would also like to see faster response times from support.

I have used this solution for three years.

The stability of this solution is good.

The solution is scalable. We currently have fifty to sixty people working within it and, now that we are using Serverless more often, we are planning to have more people working with it.

Support is good but they could be a bit faster replying to our tickets.

The initial setup was straightforward.

We had one admin complete the initial setup in ten to twenty minutes.

Price varies by use-case. You pay for the database itself in addition to any consumed data within Serverless plus other fees if you use the Data Factory that is inside.

I would recommend others to use this product but urge them to understand that it is more of a technical database used to prepare data as opposed to serving it.

I would rate this solution a seven out of ten.

We mostly provide cloud data warehousing platforms for major banks in Canada. What we're trying to do is to create a standard platform environment that is compliant with the regulatory requirements imposed by the government and financial overseeing institutions for the banks. We help them to onboard the lines of business to these platforms and migrate the existing workloads to the cloud platforms.

The ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage.

The major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse.

There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process.

When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

I have been using this solution for two years.

Generally, it is stable. We all heard about the Active Directory issue earlier this week, but it was not related to Synapse. It was related to the Azure platform.

Its scalability is good. The only thing is that when you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

We're working with banks, and they have great support because Microsoft has multiple representatives closely monitoring each account. Whenever there is an issue, they're being proactive. They're making a lot of money out of it. Most of the banks, on average, spend between 30 to 50 million a year on Azure. They're pretty large accounts, and Microsoft has dedicated people supporting everything related to Azure.

We deliver platforms to different banks. Some of the banks go with Synapse, and some of the banks go with Snowflake. Overall, these are two major alternatives available right now.

There are multiple differences in terms of the support of different workloads. When one of the banks made a decision to go with Snowflake, the major reason for it was the support for the multi-cloud environment. The major pro of Synapse is the service, and the major con is that when you decide to move out of Synapse, you would have to rewrite the entire thing, whereas, with Snowflake, it would be just simple migration to different cloud providers.

It is relatively straightforward as long as you understand what you're doing.

You don't really need to maintain it. That's the entire point of the cloud. You pay for it to be maintained. 

We do deal with monitoring and other similar things, but most of the activities are automated. Overall, it doesn't require a lot of labor around it. We're delivering the platform as infrastructure as a cloud, so everything is going through the pipeline. 

It goes by the usage, and there are some limits. Synapse goes by particular pricing, and it is expensive. Both Azure Synapse Analytics and Snowflake are pretty expensive. They don't have standard pricing. They deal with each customer differently.

For working with Synapse, you need to have an understanding and knowledge of the product to take full advantage of it. Synapse has a lot of features in terms of scalability, such as resource management, distribution, and partitioning. There are a lot of things that you need to consider when you go for it. It is not a simple database that you put in there, and it is running itself. 

I would rate Microsoft Azure Synapse Analytics a seven 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. 

We're using this solution for general data integration. We are customers of Microsoft Azure Synapse Analytics and I'm a data specialist. 

I like the solution because it's very interactive and provides flexibility. It's mostly a drag-and-drop procedure. It also provides a lot of design choices.

We've only recently starting testing this solution and it would be helpful if the documentation was better or if the company could provide some kind of presentation to help us understand how the tool works and what's required to optimize use of the solution.

We've been testing this solution for a couple of months. 

I haven't seen any issues with stability or scalability. We have an infrastructure team of around 40 people. 

The company chose Synapse Analytics because the price is fair and I understand it's cheaper than Snowflake.

We're also hoping to evaluate Snowflake which is an advanced version of both Azure and AWS together. Snowflake has advantages, especially in terms of scalability which can also be implemented separately at the storage level and also at the computer level. 

I think Synapse Analytics is definitely better than the traditional high solution data solutions that we've previously used. It's definitely worth considering and I haven't come across anything negative, only advantages for now.

I would rate this solution an eight out of 10.