Microsoft Azure Synapse Analytics Reviews

My use case for Microsoft Azure Synapse Analytics is because it's embedded in the Azure Cloud, and as a consequence, if you decide to work with Azure Cloud as my company does, this is the best choice because it's fully integrated with all the Azure Cloud tools.

For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use. There is no specific feature or tool that stands out as better than others, but because it's fully integrated, it results in very easy and efficient usage.

The initial setup of Microsoft Azure Synapse Analytics is not complex because it's fully integrated.

If we make a comparison between Microsoft Azure Synapse Analytics and Databricks, though they're not the same, many capabilities are overlapping. Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth. It has very powerful programming languages that Microsoft Azure Synapse Analytics doesn't have. From my point of view, Microsoft Azure Synapse Analytics is very well integrated and easy to use, but it remains a collection of capabilities.

Databricks makes me feel more comfortable in terms of integration between different pieces composing the solution, but that's only my opinion.

As IT Director, I have more than four years of experience working with Microsoft Azure Synapse Analytics.

I rate the stability of Microsoft Azure Synapse Analytics as acceptable; it's good enough, but not very high.

For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework. Outside is a different discussion; if you have a hybrid cloud solution, we should open another discussion for this.

When it comes to technical support from Microsoft, I am a user and when I have a problem, I open tickets to our operations team who manage it. Considering the speed they solve the problem, I think it is acceptable, but not at the required level. For very deep and high-impact problems, they react. However, for problems that they consider not so important, such as Power BI not working or Microsoft Azure Synapse Analytics not working, they are not so reactive.

This is an underestimation of the real impact because we use big data also to monitor the network and the customer. Not monitoring data results often in a big impact on customer services and customer perception. I rate it an eight for cloud virtual instances infrastructure problems and a six minus when we come to big data tools that they offer as cloud services.

Positive

Before using Microsoft Azure Synapse Analytics, I used many standalone, open-source solutions. I switched from those tools to Microsoft Azure Synapse Analytics because when we moved to the cloud infrastructure and selected Azure, it was natural to consider Databricks and Microsoft Azure Synapse Analytics as solutions along with Power BI.

The initial setup of Microsoft Azure Synapse Analytics is not complex because it's fully integrated.

I think the price of Microsoft Azure Synapse Analytics is very expensive, but that's not only for Microsoft Azure Synapse Analytics—it's for the cloud in general. The cloud is not cost-effective. It is very cost-effective if you need to speed up the first use of the solution because you want to test if the market is welcoming to these solutions. You can experiment very quickly with new solutions and develop new prototypes. It's very aligned to an agile way of developing new things. However, when you scale the solution, the cloud doesn't work anymore in terms of cost.

I would recommend Microsoft Azure Synapse Analytics to others, but they are forced to use it; it's not a free choice. If you go for Microsoft Cloud, you are forced to use Microsoft Azure Synapse Analytics. To explain further, if we compare Microsoft Azure Synapse Analytics with Databricks in Microsoft Cloud, Databricks is an open-source solution that Microsoft took inside the Microsoft Cloud farm, and this is the first option. The second option is Microsoft Azure Synapse Analytics.

When you compare both of them, if you don't need a very good development environment that Databricks offers, after making a back-to-back capability comparison, you see that when you mount Power BI on top of Databricks and the amount of data is huge, you are not able to work because it's too slow. So you are forced to put Microsoft Azure Synapse Analytics on top, and the solution is very fast.

Microsoft has optimized the connector only for Microsoft Azure Synapse Analytics and not for Databricks. For that reason, you have no option; it's not because it's better. I believe that Databricks is much better than Microsoft Azure Synapse Analytics, but because the connectors are not optimized and because Databricks is not so well integrated as Microsoft Azure Synapse Analytics, at the end, you have the perception that Microsoft Azure Synapse Analytics is much better.

There is no reason to use Microsoft Azure Synapse Analytics and to pay so much for it, but because of the integration of Microsoft Azure Synapse Analytics in the cloud since it's a Microsoft native tool, you can't say the same for Databricks, which is an open-source tool that Microsoft took inside.

I would rate Microsoft Azure Synapse Analytics overall as a seven; it's not the best.