Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
They are slow to respond and not very knowledgeable.
This is an underestimation of the real impact because we use big data also to monitor the network and the customer.
I would say the technical support for Microsoft Azure Synapse Analytics rates around six; they are friendly but there is a gap in knowledge, which makes it a little difficult to deal with.
Recovering from such scenarios becomes a bit problematic or time-consuming.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
For the scalability of Microsoft Azure Synapse Analytics, I would rate it a 10 until you remain in the Azure Cloud scalability framework.
Most of our functions or jobs are queued due to that.
I find the service stable as I have not encountered many issues.
I have faced stability issues, mainly due to the storage my organization has, though I am not sure if it's specifically due to the tool.
Many support staff lack the necessary skills to assist with our customized requests.
Databricks is a very rich solution, with numerous open sources and capabilities in terms of extract, transform, load, database query, and so forth.
The reasons I don't rate Microsoft Azure Synapse Analytics higher include data integration and tech support being two main issues.
When you scale the solution, the cloud doesn't work anymore in terms of cost.
I find the pricing of Microsoft Azure Synapse Analytics reasonable.
For Microsoft Azure Synapse Analytics, the integration is the most valuable feature, meaning that whatever you need is fast and easy to use.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
The best feature of Microsoft Azure Synapse Analytics is the notebook functionality; it provides a very good interface, and we can easily do our experiments, POCs, and check things before migration or deployment to higher environments such as from development to SIT and then production.
The product is not complex; I do not have to create stored procedures, functions, or views.
Company Size | Count |
---|---|
Small Business | 27 |
Midsize Enterprise | 18 |
Large Enterprise | 54 |
Company Size | Count |
---|---|
Small Business | 30 |
Midsize Enterprise | 10 |
Large Enterprise | 48 |
Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.
Microsoft Azure Synapse Analytics is built with these 4 components:
Microsoft Azure Synapse Analytics Features
Microsoft Azure Synapse Analytics has many valuable key features, including:
Microsoft Azure Synapse Analytics Benefits
Some of the benefits of using Microsoft Azure Synapse Analytics include:
Reviews from Real Users
Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.
PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "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."
Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."
A Senior Teradata Consultant at a tech services company says, "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."
VMware Tanzu is a robust platform tailored for data warehousing, complex analytics, BI applications, and predictive analytics. It excels in scalability, performance, and parallel processing, enhancing data handling efficiency. Users report significant productivity improvements and streamlined operations, making it ideal for comprehensive data solutions.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.