Snowflake Architecture:

It consists of three layers

Database storage Layer
Query Processing Layer
Cloud Services Layer

Database storage Layer:

When you load data into snowflake, snowflake reorganizes that data into its internal optimized, compressed, columnar format.
Snowflake stores this optimized data in cloud storage.
This is layer we store the actual data, while setting up snowflake which cloud provider you select based on that we can store the data in respective cloud storage.
We store the data in compressed columnar format than traditional row and column format.
We can store several objects like tables, views etc in this layer and we retrieve them using SQL query language.

Query Processing Layer:

- We execute the actual queries in this layer.
- To process the queries, we use virtual warehouses.
- Each virtual warehouse is MPP compute cluster composed of multiple compute nodes allocated by Snowflake from cloud provider.
- The beauty of Snowflake’s compute layer is that compute and storage are decoupled—this means you can scale them separately based on workload demand.

Cloud Services Layer: This layer is collection of services that coordinate activities across snowflake.

we can manage below services in this layer.

- - Authentication
  - Infrastructure management
  - Metadata management
  - Query parsing and optimization
  - Access control

Supported Cloud Platform: Snowflake as a self-managed service runs completely on cloud infrastructure. This means the three layers of snowflake Architecture (storage, compute, cloud services) are deployed and managed entirely on a selected cloud platform.

We can host Snowflake account on any of the following cloud data platforms

- - Amazon Web Services (AWS)
  - Google Cloud Platform (GCP)
  - Microsoft Azure (Azure)

SNOWFLAKE TRAINING:

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