Microsoft Azure Synapse Analytics Reviews

We are using Microsoft Azure Synapse Analytics with multiple customers for data integration, data migration, and data analytics. I offer these services to my customers as part of my service organization called Edge Technologies.

Customers use the solution for analytics, such as forecasting reports. There are a lot of business cases, we customized them based on the customer.

The most valuable feature of Microsoft Azure Synapse Analytics is its integration with the new legacy systems. Whatever application we want to integrate, we receive the reports based on the objects. The solution is easy to purchase from the cloud.

Microsoft Azure Synapse Analytics can improve by adding more flexibility to the reports. Having more visible structures based on the area, region and country would be beneficial.

I have been using Microsoft Azure Synapse Analytics for approximately nine months in production.

The stability of Microsoft Azure Synapse Analytics is good. However, there is a global transformation and consolidation happening.

Microsoft Azure Synapse Analytics is able to scale to the needs of our requirements.

The initial setup of Microsoft Azure Synapse Analytics is easy.

We only have to pay for what we use in the solution. It's easy for the customers. It's not more than some companies, not more than 300 to 400 users. They do not need to buy other license products, such as SAP B1, or analytics tools in the market, such as Tableau.

There is going to be competition in the market with the release of SAP Cloud Analytics.

The solution does not require maintenance because it is sized-based.

I would recommend this solution to others. I have evaluated the fact sheet on the solution.

I rate Microsoft Azure Synapse Analytics an eight out of ten.

We are a marketing company so we help our customers with marketing strategies. The marketing is based on the final customers, and we use Microsoft Azure Synapse Analytics for CDP.

The most valuable feature of Microsoft Azure Synapse Analytics is the pipeline that is the ETL tool. It's very well designed and is overall very good. We usually don't use the ETL tool in Databricks, but we use the ETL tool in this solution.

The SQL features in the solution are very good.

Microsoft Azure Synapse Analytics could improve the section in the solution where you can implement the Python Spark pipelines, it's not the same as in Databricks which would be better.

The data visualization in Microsoft Azure is provided by Power BI, it's not needed to have something in Synapse. The data governance tool is outside Synapse, but there is a data governance tool that is called Purview in Microsoft Azure. They need to improve the Spark part of the solution then it would be complete. 

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

Microsoft Azure Synapse Analytics is highly stable because it's based on SQL Server technology. It's a very old technology, which is solid.

Microsoft Azure Synapse Analytics is scalable.

I did not use another solution similar to Microsoft Azure Synapse Analytics.

The initial setup of Microsoft Azure Synapse Analytics is simple. It's a managed service in Microsoft Azure, you only need to search for it and install it.

You have to be very careful with one specific service inside Microsoft Azure Synapse Analytics which is called the Sequel Data Warehouse Dedicated. It is very reliable and performs well, but it's expensive. You need to define the tier well because you can choose between several tiers and you have to define which suits your needs and not overperform the tier because it's quite expensive.

Once a service is managed as a service in a cloud platform, the maintenance is very easy. You have to monitor it, but the maintenance infrastructure is extremely easy.

This solution is very easy once you have a Microsoft Azure subscription to go straight to Microsoft Azure Synapse Analytics because it's native. However, there are other kinds of technologies one can use. I would suggest before using this solution, look at other solutions, such as Databricks or Snowflake, and not stop at the first solution that you can receive in Microsoft Azure.

I rate Microsoft Azure Synapse Analytics an eight out of ten.

We primarily use the solution for our cloud data warehouse. 

The usability has been excellent. 

It offers good integration. 

The product works well with other Azure products.

The initial setup is very convenient.

It is scalable.

We have found the solution to be stable. 

The security is fine.

We'd like the solution to have more analytics capability.

We would like more detail on reports so that they are easy to understand in terms of usage of data and services. It could be improved.

I've been using the solution for one year. 

It's a stable product. It is reliable. The performance is good. It doesn't crash or freeze. There aren't bugs or glitches. 

We can scale the product up and down according to our needs.

We have around 100 people using the solution right now. 

My customer uses it on a daily basis.

We are satisfied with technical support. I haven't used them too much.

Neutral

I've also used Snowflake. 

Azure Synapse is a more integrated platform. With Snowflake, you need to buy it separately and run it off Microsoft. Snowflake, however, has better cost control. Snowflake is comparatively cost-efficient.

It is a straightforward setup. It's easy and not overly complex. I have not measured how long it actually takes; however, I can say the implementation is convenient. My administrator handled the setup. I did not handle it directly myself. 

The solution can get expensive, and it's hard to monitor the costs. It does depend on how you utilize it. You can configure it in a certain way.

I'd rate the solution seven out of ten. 

Microsoft Azure Synapse Analytics is used for analytics.

The most valuable features of Microsoft Azure Synapse Analytics are the interface and the agility of the on-cloud platform.

Microsoft Azure Synapse Analytics's overall integration within the Azure ecosystem could improve. The native Microsoft solution versus another solution, such as Databricks, there are areas where there could be some improvements.

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

Microsoft Azure Synapse Analytics is stable.

The scalability of Microsoft Azure Synapse Analytics is very good.

We have hundreds of people using this solution.

Compared to the traditional data center approach, the cloud has pushed forward well for maintenance reduction. There is a 60 to 80 percent reduction.

My advice to others is this solution is not meant for small databases.

I rate Microsoft Azure Synapse Analytics an eight out of ten.

Our company includes 50 analysts who use the solution on a daily basis to predict customer behavior. 

The solution's best feature is its predictive analytics. 

Integration with other vendors has limitations and could be improved. 

Integration of process analytics would be a nice addition that allows us to analyze efficiency. 

I have been using the solution for six months. 

The solution is stable. 

The solution is a web data warehousing and analytical platform built for enterprise environments, so it is definitely scalable. 

Technical support is very responsive and knowledgeable. 

I rate support an eight out of ten. 

Positive

We do not use other solutions because we operate in a Microsoft environment that is not expected to go to AWS.

The initial setup is complex and I rate it a four out of ten. 

The solution was implemented through a third-party vendor team. 

The solution has helped to predict sales and focus attention on enhancements that have improved the bottom line. 

I rate the ROI a six out of ten. 

I don't know specifics about pricing but I hear that it is quite expensive. For example, Power BI is not as expensive as this solution.  

The solution has superior modeling and predictive analytical abilities in comparison to Power BI. There isn't really an expectation that you would get these superior abilities in Power BI because the solutions have different purposes and use cases. 

I rate the solution 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. 

We use Microsoft Azure Synapse Analytics for a combination of a data warehouse with some advanced capabilities, to allow us to run some machine learning models on top of it. 

The most valuable feature of Microsoft Azure Synapse Analytics is the capabilities, and the integration with other Azure resources, such as Data Factory, Databricks, and Spark for data processing. The overall ability to compose the solution with other Azure resources is valuable.

Microsoft Azure Synapse Analytics could improve in usability. I have found the same issue with all Microsoft solutions.

I have been using Microsoft Azure Synapse Analytics for approximately 10 months.

Microsoft Azure Synapse Analytics is stable.

The scalability of Microsoft Azure Synapse Analytics is very good.

We have approximately 40 people using the solution. We have plans to increase our usage in the future.

I rate the support from Microsoft Azure Synapse Analytics a three out of five.

Neutral

I did not use another solution prior to using Microsoft Azure Synapse Analytics.

The initial setup of Microsoft Azure Synapse Analytics is straightforward. The full process took a couple of weeks when we started and finished.

We did the implementation of Microsoft Azure Synapse Analytics in-house.

We have a cloud services team with approximately three or four people and they take care of everything we need to support Microsoft Azure Synapse Analytics.

It's difficult to compute a return on investment in data analytics.

The price of Microsoft Azure Synapse Analytics can vary. Other solutions are typically fixed prices and a fixed cost regardless of usage, but this solution is based on usage or consumption.

The best comparison for Microsoft Azure Synapse Analytics would be with or against Snowflake. The only difference is that Microsoft Azure Synapse Analytics is more modular. If you want to build something very complex, you can. However, if you want to do something simple, you could stick with easy-to-use, more integrated platforms, such as Snowflake.

My advice to others is they should leverage other Azure components if they can. If they are looking for an integrated solution that's easy to use, they should look at competitors.

I rate Microsoft Azure Synapse Analytics an eight out of ten.

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.

Negative

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.