Snowflake is a cloud-based data warehouse solution that operates as a Software-as-a-Service (SaaS). A relatively new entrant in the market, Snowflake has already disrupted the market majorly, grabbed a significant amount of market share, and reached new levels of popularity. There can be many convincing reasons to use a Snowflake data warehouse instead of other methods.
Let’s take a look at some of the most important reasons why you might benefit by choosing Snowflake for your data warehouse.
Why use Snowflake as a data warehouse solution?
The most compelling argument to use a solution like Snowflake is the flexibility, scalability, and features you can put to good use while completely negating the need for expensive and unwieldly on-premise infrastructure. Snowflake also provides several benefits and features that are inherent in its design, making the process of working with data much simpler.
For starters, it is incredibly easy to move data into Snowflake by using an ETL solution. The architecture of Snowflake offers myriad workflow opportunities as the storage component and the compute component can scale independent of each other.
This means that you can pay for exactly as much storage and compute power you need, with the option of immediately expanding one or both whenever the need arises. Therefore, this is a scalable solution with no wasted resource.
The architecture of Snowflake is intuitive and consists of three layers. The database storage can hold structured and semi-structured data while Snowflake can manage important parameters like file structure, file sizes, compression, statistics, and metadata. The compute layer uses virtual warehouses or cluster to interact with the data and perform compute operations completely independently, therefore sharing zero resources with the storage layer.
On top of all this, there is a layer of cloud services that can help with infrastructure management, authentication, metadata management, query optimization, and access control. Since Snowflake is designed from the ground up to be a cloud-based solution, a lot of the problems inherently present in older solutions based on physical hardware can be completely eliminated from the scenario. You do not have to contend with administration and maintenance costs, scalability issues, hardware breakdowns, or lack of compute power.
You have complete control over the speed and power of the compute layer by choosing to pay for a more powerful engine in accordance with your needs. You can also scale down if you want, when you want. This guarantees superior speed and performance without any wasted resource. The storage layer is also capable of housing both structured and semi-structured data, making it a versatile storage solution that allows for immediate storage of time-sensitive data without any need for pre-processing.
In traditional data warehouses, there are often concurrency issues caused by too many simultaneous users or queries. These kinds of problems are a thing of the past with Snowflake, which makes use of a multi-cluster architecture to keep queries confined to their own virtual warehouses. On top of this, there are myriad options for easy, seamless sharing of data and excellent security features built into the platform.
Why use a Snowflake cloud data warehouse instead of an on-premise data warehouse?
Compared with an on-premise data warehouse, in most cases Snowflake can be a much more efficient, cost-effective, and practical solution that brings many more features to the table. The most basic consideration is the high costs of maintaining an on-premise platform, coupled with its inherent inefficiency and problems, none of which would affect you if you move to Snowflake.
You pay for only what you end up using, leverage the faster and more versatile platform to decrease time to market, and remain in complete control over your storage and compute clusters without having to worry about maintenance and security.