Microsoft Azure Synapse Analytics Reviews

We run our finance and supply chain jobs using SQL BW, and we visualize our data loads on Power BI. We are using SQL Data Warehouse for data warehousing.

In terms of cost savings, we don't need specialization in skills as advanced as Teradata. We used to pay extensive licensing fees for Teradata, which we no longer pay. Azure Synapse has provided scalability and ease of use, especially when looking at performance tuning and optimization.

The biggest benefits are scalability and ease of use when looking at performance tuning and optimization. SQL Data Warehouse is very scalable. Microsoft Fabric brings a lot of value.

We will start looking at Microsoft Fabric for further improvement as it brings more value. Also, managing workloads and data transformation using Databricks should be a focus.

I have been using SQL Data Warehouse for the last three years. We completed our final migration to SQL Data Warehouse last October or November.

We haven’t faced many issues. Stability has been great, so I would rate it about a nine out of ten.

I would rate the scalability of the solution ten out of ten. It is very scalable.

They have been very responsive. We have a company in South Africa that reaches out to us, and if they can't resolve the issue, they hand us off to Microsoft. Customer support's responsiveness and quality are rated as a seven.

Neutral

We moved away from Teradata about a year ago. We used to pay extensive licensing fees for Teradata.

The setup was very easy. I would rate it as a ten out of ten for ease of setup.

We have seen a return on investment because it’s not as specialized as Teradata, and we no longer pay extensive licensing fees.

The cost is reasonable for our company. There is no license cost; we pay only for Azure Compute's costs. It is important to manage the cost efficiently on a daily basis.

Definitely, it's the right approach. Always monitor your costs and optimize your database's performance.

I'd rate the solution eight out of ten.

It can be used for reducing hardware expenses.

It is a highly stable solution and it's easy to use. 

The security performance and cost are the two things that needs improvement. 

I have been using Microsoft Azure Synapse Analytics for eight years. 

It is a stable solution.  

It is a scalable solution.  

The initial setup is easy. It does not take much time to deploy the solution. 

You have to go to the resources and the security SSC group and the system for deployment. It can be done in-house. 

We have a licensing cost to pay. 

Overall, I would rate the solution a nine out of ten. 

We use the solution for data storage.

The product is easy to use, and anybody can easily migrate to advanced DB.

Adding more transformations and plugins to the solution is very important.

I have been using Microsoft Azure Synapse Analytics for 10 years.

I rate the solution’s stability a seven to eight out of ten.

Around 20 to 30 users, including developers and architecture engineers, regularly use the solution for migration purposes. For a small organization, fewer people would be required for the migration.

I rate the solution a seven to eight out of ten for scalability.

The solution provides good technical support. The support team's response time depends on the issue's criticality. They will call you back in two or three hours if the severity is high. If the severity is low, they will take more than 24 hours.

Microsoft Azure Synapse Analytics is a moderately priced solution. We pay a yearly licensing fee for the solution. If you get help from partners, it will be expensive for you.

Microsoft Azure Synapse Analytics is a cloud-based solution. Since we are migrating, the cost is high. We assume the cost will be reduced post-migration, increasing the company's profitability. Microsoft Azure Synapse Analytics will be more profitable for any company in the long run. I would recommend the solution to other users.

Overall, I rate the solution an eight out of ten.

Our company uses the solution to mine generous amounts of data for customers. We are partners with Microsoft and are totally dependent on the solution. 

Synapses are very good and can deal with petabytes of data. 

The solution has far better synapse analytics than Redshift. 

The solution handles single or complex items within a second. 

Power BI is a great management tool that has email in the synapse itself so you can move regulations. 

The solution does not support oriented scaling in the synapse. 

I have been using the solution for seven months. 

The solution is stable and properly distributes all kinds of data including symmetric multiprocessing. 

The solution is scalable.

I have not needed technical support. If I have an issue, there is always another staff member who can assist. The staff can solve complexities within seconds. 

The setup is quite easy and similar to Jira. 

We implement the solution for customers. 

Deployment can take some time because you first have to collect and develop the data through client relations. This can cause lags. 

The computer and storage costs are totally separate which allows you to work independently or manage costs. 

In contrast, Redshift combines both costs. 

The solution is far better than Redshift in terms of secondary indexing and the level of international support.

It is easy to migrate data to the solution from other clouds, even for big organizations. A complete migration can be done in less than ten hours.  

The solution is better than other cloud platforms so I recommend it. 

I rate the solution a nine out of ten. 

The good thing about Synapse is the scale factor. It can handle a lot more volume of data compared to Azure SQL. There is Azure SQL, and there is a SQL Data Warehouse, which is now called Synapse. SQL is for smaller databases, and SQL Data Warehouse (Synapse) is for larger databases. Performance-wise, if you process a huge amount of data, SQL Data Warehouse is good due to its parallel processing capability. It's scalable. 

The setup is pretty simple. 

It's stable. 

In Azure, when you do the scaling up, it is not totally simple. It takes time to scale up. It actually kind of rebuilds the database behind this when you scale. If I am utilizing 1,000 of what they call the Data Warehouse and you need 1,200, there is downtime required.

There is a limit on the number of concurrent queries to around 125 for Azure Synapse.

I've been using the solution for a while at this point. 

The solution is pretty stable. The dedicated pool is pretty stable. It can handle quite a heavy workload.

The product can scale. 

For one of my clients, it was used as an Enterprise Data Warehouse, so it has got all kinds of insurance functions, and users. It has got an underwriting team, it has got the actual team, it has got a claims operations team, et cetera. All the enterprise Data Warehouse users start consuming data while using the visualization tools like Boll-BI, and then MicroStrategy, et cetera.

The initial setup is not complex. It's pretty simple and straightforward. 

There was a pool of DBAs that maintain all the Data Warehouse on-premise and cloud. There were hundreds of databases, and this is just one of the databases added to that list. The DBA team is comprised of five to six DBA team members.

I'm not sure of the exact cost, however, it is around $100,000 a year. 

We are Microsoft partners. 

Potential customers should check out the ease of management. This solution is easier to maintain compared toother options. 

I'd rate the solution seven out of ten. There are some challenges related to this replication and then there is quite a lot of design thinking to be done.

We are ingesting data from different sources and using Power BI for reporting and decision-making for analytics.

It helps centralize our data and create one source of truth, helping us become a data-driven organization.

The fact that we can ingest from different types of sources, whether they are internal systems or external sources. It also offers insights and proposes what we can use with that data.

I wish the data governance feature could be incorporated without requiring an additional license.

We have been working with it for two to three years.

The stability of Synapse Analytics is rated as ten. It is very stable.

The scalability of Synapse Analytics is also rated as ten. It is meant for big data and is scalable based on how much we want to use.

If they have allocated a resource, like a task team to assist, then they do a good job. However, if you log a general call, it will take longer. Dealing directly with the account manager is quicker.

Neutral

We used products from other vendors before, but now we primarily use Microsoft.

It took about twelve months because of the complexities related to ingesting data from different sources.

Microsoft offered us a FastTrack team that guided us. From our side, six engineers took part in the deployment.

At this point, I cannot put the financial benefit.

It is not a cheap solution. That said, it is reasonable compared to its peers.

Overall, Microsoft Azure Synapse Analytics offers good integration, is user-friendly for data analysts, and helps in centralizing data.

I'd rate the solution ten out of ten.

We use the product to transform the data from the on-premise environment to the cloud. It is a flexible platform and integrates with multiple data sources.

The platform has multiple valuable use cases. They include performance, compatibility, flexibility, and cost.

Microsoft Azure Synapse Analytics's pricing could be reduced.

We have been using Microsoft Azure Synapse Analytics for five years.

I rate the platform's stability a seven or eight out of ten. It could be improved.

We manage four to five Microsoft Azure Synapse Analytics customers in our environment. It is a scalable software.

The initial setup is easy using the infrastructure code. The deployment takes a maximum of a day to complete as we conduct a POC enrollment before the setup. It helps us understand the process. Later, we develop it in the production environment.

We need assistance from a third-party vendor for product implementation.

I am evaluating Oracle GoldenGate. However, it is a licensed software that induces extra costs. Instead, I want to utilize Microsoft cloud services to their full potential and avoid additional licensing costs. By doing so, I aim to reduce reliance on Oracle software throughout the migration journey, opting for cloud-native solutions that align with the goals of cost-effectiveness.

Many customers prefer using Microsoft Azure Synapse Analytics. It allows them to develop applications in Java and .NET. It provides security, flexibility, and efficient UI as well. It enables the ease of configuring APIs and overall configurability. As a certified cloud specialist, I advise others to consider use cases and requirements while purchasing.

I rate the product an eight out of ten.

When this application is in use, it's utilized to extract data and observe its performance and behavior. It also helps to make adjustments to fine-tune the application.

Azure Synapse combines the strengths of SQL technologies for effective enterprise data management. So, essentially, it excels in managing enterprise data.

I'm not very certain about suggesting specific improvements, but Microsoft consistently introduces enhancements, approximately on a quarterly basis, which is commendable. It could be beneficial to focus on integration with various data sources and similar enhancements. I noticed they have already integrated Power BI, which is advantageous. These developments are gaining prominence, and perhaps incorporating generative AI and leveraging it could be part of their future plans. 

It also provides both serverless and dedicated resource models. Azure Synapse already incorporates SQL machine learning models to some extent, but I anticipate that it will offer even more comprehensive AI capabilities in the future.

I have been using Microsoft Azure Synapse Analytics for the past six months.

Azure products are highly scalable, so I would rate it nine out of ten. 

It is good most of the time, but it can be improved.

Positive

Before Microsoft Azure Synapse Analytics, we used different technology but shifted mainly because of the scalability.

If the person has a general understanding and some basic knowledge of the subject, setting it up shouldn't pose a significant problem or challenge. I would rate the setup an eight out of ten.

There are multiple teams, each with their individual setups, while the overall backend configuration and maintenance tasks are handled by a dedicated team. This team might be a global team consisting of more than twenty members who manage these responsibilities.

Microsoft's pricing is relatively high, and it varies according to the extent of our usage. The pricing is directly tied to our consumption. This decision is ultimately a business choice.

There were tests conducted alongside Microsoft Azure, although Azure was the preferred partner for our organization. It's important to note that the choice isn't solely based on price or the best product; sometimes, it's driven by the existing setup running on a particular platform, leading to the selection of the best available option.

There is a need to analyze the business objectives and technical needs before making a decision. If Synapse aligns with your business goals and meets your data warehousing requirements, you can proceed. Additionally, it's advisable to conduct price and scalability assessments and perhaps carry out a small proof of concept (POC) using production data before making a final decision.

I would rate the solution an eight out of ten.