The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.
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Azure SQL Database
Score 8.3 out of 10
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Azure SQL Database is Microsoft's relational database as a service (DBaaS).
We use these tools for applications they are better suited for vs a Snowflake. For e.g. MS Fabric has powerful agentic AI capabilities; Redshift is our go to choice for the TMT vertical within the organization and Databricks is the default choice for AI/ML applications.
Snowflake provides various features, such as integration with Python using Snowpark. The reporting feature that caters to your small reporting needs is Snowsight. The Snowflake data marketplace is where you can get multiple data for free and even some of the data which you can …
These are comparable products that can make sense depending on the specific needs of your organization. All are certainly serviceable and have varying pros and cons. Snowflake seems to provide the greatest degree of flexibility and easy scalability as new data gets brought into …
We needed scalability and a new way of organizing our data; Snowflake allowed us to have a clearer view of our data warehouses and schemas. Snowflake is also way superior in terms of speed and quick insights from the raw data you query, which is very valuable to us.
Snowflake has an attractive pricing model with auto-suspend and auto-resume and pay per use. AWS Redshift requires higher administrative efforts to maintain and scale the platform whereas with Snowflake those admin tasks are not needed or automatically taken care of.
We had a MS SQL server with over 2 TB of ram & 51 processors that we were using, that could no longer handle our workload. Snowflake can handle 3 times that workload with ease and efficiency.
Snowflake is much faster and easier to write queries and pull data. But the visualization part of Snowflake is not as good as them. Also, Snowflake only supports SQL queries but not python or other languages. So basically Snowflake is the expert in its field but not suitable …
We particularly liked Snowflake's security model as well as its unique storage (whereby everything is essentially a pointer to immutable micro-partitions, which is the key behind its zero-copy cloning, its secure sharing, its time travel, etc.). and also how it separates …
While Snowflake is more open to cloud eco system, SAP integrated well with SAP eco system products like SAP ECC or SAP S/4. So for people who have invested heavily in SAP eco system including SAP ECC or S/4, it makes sense to go with SAP DWC which is also evolving very rapidly. …
In my opinion, the other tools have similar and some different features; however, when I ran proof of technologies between Synapse and Snowflake. Snowflake did things better or just had functionality that the other tools did not. One that stuck out at the time was scale up …
Each of the other solutions were cloud vendor specific, Snowflake can ride on either Amazon Web Services, Microsoft Azure, or Google Cloud. The fact that they are ANSI-sql compliant and have an effective means of offloading data makes them portable and easy to sell to teams …
Azure and Snowflake compared very similarly, but Snowflake provided more options to integrate and connect with tools/companies that were not partners. It seemed to be a more flexible environment. The barrier for entry on Oracle and Google we just too complicated. In particular, …
I have had the experience of using one more database management system at my previous workplace. What Snowflake provides is better user-friendly consoles, suggestions while writing a query, ease of access to connect to various BI platforms to analyze, [and a] more robust system …
Snowflake has won the match because it is giving an excellent performance with its efficient features and reliable results. This is a totally secure program for our precious and important data.
Our initial data warehousing solution was Treasure Data. We had issues with the costly pricing model, which would be exhorbitant if we want to hold our data in memory and query using Presto. As a result, some heavy lifting was done in Hive (managed by Treasure Data); …
In my experience running the data management practice at InterWorks, we believe that cloud data warehouse products will eventually serve the majority of data warehousing use cases and power data analytics at most companies. Of this cohort, we believe that Snowflake is the best …
Redshift compute and storage can be scaled up/down together (though they added some features recently, they don't quite add up). I haven't tried Avalanche or Firebolt but would love to in the near future, due to their pedigree or revolutionary billing methods.
- Cost was the main aspect on the decision. - Performance was in par or better compared to other tools in the market. - Snowflake in my opinion stacks better than other tools I have used in the past.
Accommodates future data types such as JSON and XML. Scalability is another advantage. Pay per use is beneficial for organizations like yours. Direct connectors with AWS help us to go with it. No limit on user creation and clone data not eating up extra disk space are a few …
Since we switch from amazon redshift to Snowflake, we found Snowflake is much better than redshift in many ways, including the data integrate and data pull. However, comparing directly pull data from amazon s3, Snowflake is quite slow in terms of data pull speed and the more …
Compared to Amazon Redshift, Snowflake is slightly easier and faster to achieve ROI but based on the user's perspective, the two tools have very little difference since both are leveraging SQL to pull data from AWS S3. Snowflake is also working with Microsoft Azure but it is …
Our issue with Redshift was that it was very expensive. On top of that, queries were still slow and if we used more of Redshift's memory, then it would have cost even more. Snowflake is not cheap, but less costly for us. Plus, the performance was much better. Also, we got to …
Better and more useful automation tools are available. Better at scaling and hosting your data. Greater security around access of data and encrypting where required. Allows for seamless integration in other Azure solutions which allows for greater flexibility when using the …
Depending on the use case they stack up very well. Google and AWS are well suited multi-cloud strategies or those that need a high level of RDS performance.
Mainly response time. Azure SQL Database is very fast and very reliable when it comes to executing queries and gathering the data results. Also, the exporting options it gives are far exceeding expectations and enable users to accommodate any deliverable in a timely and …
I selected Azure SQL because it integrates nicely with the technology stacks we currently maintain. The pricing is right, and clients are happy with that. Scaling is easy. Most of our clients don't want to maintain a full-blown database server, and they don't need one. For …
The simplicity and great features and good support of Microsoft as well as the more reasonable flexible price than other competitors is one of the important reasons for choosing it.
Oracle database is "the" serious database. There really is no competition in that field. SQL Database would be a serious competitor through the ease of implementation and the "no maintenance," but since it's too expensive for "normal" use (medium to small applications), it just …
It is very easy to setup SQL database on Azure. one can always refer to their documentation for best practices. It is highly available and scalable. It is cheaper than its alternatives and provide better performance than others. As we are using many other services of Azure for …
Director, eCommerce Analytics and Digital Marketing
Chose Azure SQL Database
The Azure SQL Database, compared to our on premise SQL server installation, is much easier to use in terms of seeing database diagnostics. There is a whole visualization platform that comes with the tool that will allow your database administrator to see what jobs are tying up …
Amazon's RDS offering is actually very good and is used in other parts of the company, we just have a lot of Azure experience so wanted to leverage that.
Being able to manage our databases in the cloud, scale quickly, and only require access to VMs made choosing Azure a no-brainer over a traditional SQL Server installation/integration. We don't have the budget or resources to integrate and maintain servers on our own, so using …
I would say MySQL in either Aurora or MariaDB form come close however, Azure SQL Database has a more streamlined approach to delivering a consistent programmability model, supported drivers and feature set.
Azure SQL Database T-SQL is advantageous and more complete than SQL …
Azure owned by Microsoft who owned SQL Server, so provided a variety of tools for easy migration/transition and from on-premises to the cloud; and management. I recommend using Azure for any on-prem SQL server databases.
Azure SQL is a clear upgrade to SQL Server 2012 and pretty much has the advantage with all the extra features that it has. Security, queries, exporting tables, T-SQL has all improved. Transitioning 18+ years of an in-house database to the cloud was a struggle, but for the …
We moved away from Oracle and NoSQL because we had been so reliant on them for the last 25 years, the pricing was too much and we were looking for a way to cut the cord. Snowflake is just too up in the air, feels like it is soon to be just another line item to add to your Azure …
Amazon Relational Database Service is the other obvious competitor. We were already in Azure, so it's not a serious contender for our business due to that bias already, but I do personally find the marketing and documentation of RDS more intimidating to sort through.
Comparing with Amazon Aurora: Azure SQL DB is 100% compatible with SQL Server and Aurora is compatible with MySQL and PostGreSQL. Because of if, SQL DB suits large enterprises with hundreds of databases better. Comparing with Oracle: the main issue is that Oracle will try to …
It stacks up in different ways, for the most part, I think Microsoft is doing a really good job versus the competition. They basically started database type products from the beginning. I've always been excited about updates and can see their progress over time. Get's me really …
If you need a quick query, snowflake is the way to go. It's super simple and scalable; we were struggling before with Azure, and with Snowflake, everything runs smoothly, and we have more control over our schemas and warehouses. Snowflake, in my opinion, is the next step when you want to scale your business and manage data. If your company is still small, there may be cheaper options.
Your upcoming app can be built faster on a fully managed SQL database and can be moved into Azure with a few to no application code changes. Flexible and responsive server less computing and Hyperscale storage can cope with your changing requirements and one of the main benefits is the reduction in costs, which is noticeable.
Snowflake scales appropriately allowing you to manage expense for peak and off peak times for pulling and data retrieval and data centric processing jobs
Snowflake offers a marketplace solution that allows you to sell and subscribe to different data sources
Snowflake manages concurrency better in our trials than other premium competitors
Snowflake has little to no setup and ramp up time
Snowflake offers online training for various employee types
Scalability is #1: if it used to be an almost no-win endeavour to try to modernize your server or migrate to other hardware, with Azure SQL Database it becomes a press of a button.
All the tools simply work after you are on Azure SQL Database.
The applications do not need changes in order to start using Azure SQL Database.
Hybrid Cloud scenarios will work.
Clustering and failover - already there.
You can start monitoring the use and extract performance insights in a new way in Azure.
Do not force customers to renew for same or higher amount to avoid loosing unused credits. Already paid credits should not expire (at least within a reasonable time frame), independent of renewal deal size.
A little slow on processing complex or large Views. We use a lot of Views to feed our BI system, and the processing time could see some improvement, IMHO.
Additional monitoring components would be nice too, automating some built in performance measurement tools would be a nice feature.
Price can always be improved as well. It’s not bad, but room for improvement.
SnowFlake is very cost effective and we also like the fact we can stop, start and spin up additional processing engines as we need to. We also like the fact that it's easy to connect our SQL IDEs to Snowflake and write our queries in the environment that we are used to
The interface is similar to other SQL query systems I've used and is fairly easy to use. My only complaint is the syntax issues. Another thing is that the error messages are not always the easiest thing to understand, especially when you incorporate temp tables. Some of that is to be expected with any new database.
The interfaces are intuitive once you are familiar with all the functions. The ability to use different tools to interact with the platform, such as directly via a browser or code editors such as VS Code or Visual Studio is a great option and allows for integrating withn the project and other testing and developing tools.
We have had terrific experiences with Snowflake support. They have drilled into queries and given us tremendous detail and helpful answers. In one case they even figured out how a particular product was interacting with Snowflake, via its queries, and gave us detail to go back to that product's vendor because the Snowflake support team identified a fault in its operation. We got it solved without lots of back-and-forth or finger-pointing because the Snowflake team gave such detailed information.
We give the support a high rating simply because every time we've had issues or questions, representatives were in contact with us quickly. Without fail, our issues/questions were handled in a timely matter. That kind of response is integral when client data integrity and availability is in question. There is also a wealth of documentation for resolving issues on your own.
Snowflake provides various features, such as integration with Python using Snowpark. The reporting feature that caters to your small reporting needs is Snowsight. The Snowflake data marketplace is where you can get multiple data for free and even some of the data which you can buy according to your needs. And the integration options with various tools like Sigma are add-ons.
I selected Azure SQL because it integrates nicely with the technology stacks we currently maintain. The pricing is right, and clients are happy with that. Scaling is easy. Most of our clients don't want to maintain a full-blown database server, and they don't need one. For them, Azure SQL is the right size.