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.
Its ability to optimize the cost with features such as Pause/Auto-resume Compute engines (aka warehouses), a zero-copy clone of tables, zero cost to xfer AWS s3 files to tables within the same region, monitor cost using snowsight dashboards, etc.
It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well.
All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse.
The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management.
It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure.
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.
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.
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.
Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services.
The cloning functionality has been the most valuable. I have been able to completely copy databases. The data sharing concept is also useful. As compared to, for example, SAP, Snowflake is a lot more open, and it allows a lot more connectivity for other providers than an SAP ecosystem.
The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.
They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises.
I work at an Insurance company with 5000+ employees and I'm interested in the collective view here.
Does anyone have a view on how Matillion ETL functionality compares to ADF for Snowflake integration, when ADF and Snowflake are hosted on Azure?
Note: Azure hosting is important, as ... Read More »