"The solution's scalability is very, very good. It's one of the most important aspects for us."
"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 most valuable feature is the level of processing power, and being able to complete tasks in parallel."
"The product is very user friendly."
"Technical support is okay in terms of the help they provide."
"They are available on the Cloud, and the platform is very intuitive."
"We have found that it is easy to develop and to do the analytics in the modules of data."
"It's user-friendly and has a good dashboard."
"The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
"The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
"It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud. It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it."
"Its performance is a big advantage. When you run a query, its performance is very good. The inbound and outbound share features are also very useful for sharing a particular database. By using these features, you can allow others to access the Snowflake database and query it, which is another advantage of this solution. It has good security, and we can easily integrate it. We can connect it with multiple source systems."
"Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
"It's ultra-fast at handling queries, which is what we find very convenient."
"The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do."
"Snowflake is an enormously useful platform. The Snowpipe feature is valuable because it allows us to load terabytes and petabytes of data into the data mart at a very low cost."
"Microsoft should develop an interface to make it easier to shift from on-premise to the cloud."
"The macro functions, though useful, are not totally user-friendly. Some people have difficulties in learning them."
"Documentation could be improved."
"I would like to see them provide the ingestion of images."
"If I'm looking for something good in the cloud, I would want it to have better standard connectors."
"It's a complicated product."
"The performance and data consistency need to be improved."
"Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better."
"There is a need for improvements in the documentation, this would allow more people to switch over to this solution."
"They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that."
"Their UiPath, the workspace area, needs some work."
"It's not that flexible when compared to Oracle."
"Its pricing or affordability is one of the big challenges. Pricing was the only thing that we didn't like about Snowflake. In terms of technical features, it is a complete solution."
"It would be better if they had a data profile tool that tells me where the gaps are in my time series data."
"They should improve the reporting tools."
Azure SQL Data Warehouse is a Fast, flexible, and secure analytics platform for the enterprise. Azure SQL Data Warehouse lets you independently scale compute and storage, while pausing and resuming your data warehouse within minutes through a massively parallel processing architecture designed for the cloud. Seamlessly create your hub for analytics along with native connectivity with data integration and visualization services, all while using your existing SQL and BI skills.
Snowflake provides a data warehouse built for the cloud, delivering a solution capable of solving problems for which legacy, on-premises and cloud data platforms were not designed.
Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 34 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 41 reviews. Microsoft Azure Synapse Analytics is rated 7.8, while Snowflake is rated 8.4. The top reviewer of Microsoft Azure Synapse Analytics writes "Scalable, intuitive, facilitates compliance and keeping your data secure". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Microsoft Azure Synapse Analytics is most compared with Amazon Redshift, SAP BW4HANA, Apache Hadoop, Oracle Autonomous Data Warehouse and AWS Lake Formation, whereas Snowflake is most compared with Amazon Redshift, Vertica, Teradata, Oracle Exadata and AWS Lake Formation. See our Microsoft Azure Synapse Analytics vs. Snowflake report.
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