Snowflake

Introduction & Architecture

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Snowflake is a cloud-based data warehousing and analysis purpose which enhance the organization to store and manage the data.
Snowflake architecture is built on cloud platforms like AWS(Amazon Web Services), Microsoft Azure and GCP(Google Cloud platform).
Snowflake Architecture:

Storage layer: It is the central part of the snowflake and is responsible for storing and data management.

Key aspects of the storage layer:

1)Cloud Storage

2)Data Protection

3)Data Replication

4)Columnar Storage

5)Micro-Partitions

6)Metadata Management
Compute layer: Responsible for query processing, executing workloads, and performing computations on data stored in the storage layer.

Key aspects of the compute layer:

1)Virtual Warehouses

2)Concurrency and Scalability

3)Query Execution

4)Dynamic Optimization

5)Elasticity and Auto-Scaling

6)Data Movement

Service layer: Encompassing the storage, computing, and management of data, Snowflake provides a comprehensive set of services and functionalities.

1)Data Warehousing

2)Query Processing and Optimization

3)Data Sharing and Collaboration

4)Security

5)Data Integration

6)Monitoring and Management

7)Administration

Snowflake support multi-cluster shared data architecture for the data processing to handle a large amount of data.

Multi-Cluster shared data architecture: The multi-cluster shared data architecture in Snowflake divides and processes workloads efficiently, regardless of their scale or complexity. By separating compute and storage layers, Snowflake enables parallel execution of queries across multiple virtual warehouses, ensuring optimal performance and resource utilization. This architecture empowers it to seamlessly handle a wide range of workloads, delivering high scalability, concurrency and reliable results.