Head of Business Integration and Architecture at Jakala
Real User
Top 5
2022-10-21T13:22:26Z
Oct 21, 2022
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.
Founder and Managing Director at a tech services company with 1-10 employees
Consultant
2022-08-24T16:30:10Z
Aug 24, 2022
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.
Learn what your peers think about Microsoft Azure Synapse Analytics. Get advice and tips from experienced pros sharing their opinions. Updated: November 2022.
Director of Systems of the TCESP at a government with 501-1,000 employees
Real User
Top 5
2022-03-03T09:24:13Z
Mar 3, 2022
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.
BI Consultant at a tech services company with 11-50 employees
Consultant
Top 10
2021-10-22T18:44:48Z
Oct 22, 2021
The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit.
We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for difference sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on.
Co Founder & CTO at a manufacturing company with 1-10 employees
Real User
2020-10-19T09:33:00Z
Oct 19, 2020
Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across.
Software Engineer at a educational organization with 501-1,000 employees
Real User
2020-10-11T08:58:07Z
Oct 11, 2020
I like its performance. It is well-structured and offers a lot of practical options. Because of the visual design of the product, it is very easy to find icons and other visual elements.
It took me more than two weeks to understand how it works. I had an intensive training session to understand it, which was enough. It was not hard to understand how it works.
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.
Sr. Teradata Consultant at a tech services company with 201-500 employees
Consultant
2020-07-29T07:45:56Z
Jul 29, 2020
Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task.
Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different databases. It scales very easily and has a good cost-benefit ratio. It is very powerful and performs well. The data processing is very fast and can do analytics on the fly.
Amazon Redshift should have more cloud-native tools that integrate with it as Microsoft does with the Azure ecosystem. There is some missing functionality that can make Redshift difficult to work in. If you are analyzing a lot of data, the load performance-wise can be very low.
Microsoft Azure Synapse Analytics can handle large amounts of data - in the petabyte range. You can scale up and down as much as you want. It has a pay-as-you-go protocol, so you only pay for what you use. The speed is very good and the architecture is excellent. You are in control of what you need, which is a huge advantage.
Microsoft Azure Synapse Analytics can be a very complicated product to use. The setup can be very complex. We had some issues with dashboard reporting - we found there were bugs in the platform when dealing with specific types of queries. This solution did not meet the necessary security protocols for some of our clients.
Conclusion
Both of these solutions are very stable, scalable, and flexible. Each of these products has their own unique ecosystems that are very competitive with each other, making them both great solutions to use. Although they are very similar, there are some features and functionalities that make them unique and attractive depending on the type of enterprise you operate. We are a smaller enterprise and overall our team felt based on ease of use, support, and where we are headed, we have started to migrate everything over to an AWS ecosystem and chose Amazon Redshift. It is the solution our clients liked best as well.
If you are dealing with semi-structured data like json Snowflake has great support in handling and querying json data. it is also good to use as data lake and can act as one stop solution for a data lake and cloud data warehouse.
query performance and low maintainability is also what makes snowflake a great choice.
Download our free Microsoft Azure Synapse Analytics Report and get advice and tips from experienced pros
sharing their opinions. Updated: November 2022.
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 setup is pretty simple.
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.
The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge.
Synapse Analytics' best feature is its ability to process large files.
The solution can scale.
It's scalable; you can scale up and scale down.
I like SQL post, which is for storage and distributed computing. Another good feature is the copy activity.
The initial setup is very simple.
I have not used the technical support from Microsoft Azure Synapse Analytics, but I worked with the developers at Microsoft who were top-notch.
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.
This is a stable solution with many functionalities.
The solution offers strong scalability opportunities.
Its seamless integration with Azure services is most valuable. If somebody wants to use all Azure services, it is the best solution.
Fills the gap between big data and classic data warehouses.
The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit.
We've had a good experience with technical support in general.
The most valuable features of Microsoft Azure Synapse Analytics are how easy and quick it is to set up the linked services.
The features most valuable are the simplicity, how easy it is to create a dashboard from different information systems.
Overall deployment and integration is pretty fast.
The whole solution is interesting for us.
The useability, the user interface, is very user-friendly.
The solution's scalability is very, very good. It's one of the most important aspects for us.
Very interactive and provides flexibility.
The stability is pretty good.
We have found that it is easy to develop and to do the analytics in the modules of data.
The pricing seems to be quite fair.
We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for difference sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on.
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.
The architecture, including compute and storage, is good.
They are very reliable and cost-effective.
It's user-friendly and has a good dashboard.
The most important feature for me is the integration with PolyBase.
The product is very user friendly.
Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across.
I like its performance. It is well-structured and offers a lot of practical options. Because of the visual design of the product, it is very easy to find icons and other visual elements.
It took me more than two weeks to understand how it works. I had an intensive training session to understand it, which was enough. It was not hard to understand how it works.
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 are available on the Cloud, and the platform is very intuitive.
The speed is great and the architecture is excellent.
The most valuable feature is performance gains.
Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task.
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.
The most valuable feature of the solution is the analytics and that it can connect with Power BI.
The most valuable feature is the incremental load because we do not need to refresh the entire data on a daily basis.
Azure elasticity allows us to scale as much as we want, and it is pay-as-you-go, so we can scale up as we need to.
The features we've found most valuable for data warehouses is extracting data, SSIS packages, and the DBs.
The main advantage of using this solution is its ability to scale and handle very large amounts of data, in the petabyte range.
The most valuable feature is the scalability.
The MPP (Massively Parallel Processing) architecture helps to make things a lot faster.
The initial setup was really easy and straightforward.
The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS.
Scaling this solution is easy and the uptime is okay.