How do you compare the cost and scalability of snowflake schema vs snowflake database?

1 Snowflake schema

Snowflake schema is a type of star schema, which is a data model that consists of a central fact table that contains the main measures and dimensions of the data, and multiple dimension tables that provide additional attributes and hierarchies for the fact table. Snowflake schema differs from star schema in that the dimension tables are further normalized, meaning that they are split into smaller tables to reduce data redundancy and improve data quality. For example, instead of having one table for product information, you might have separate tables for product category, product subcategory, and product details. This creates a snowflake-like shape when you draw the relationships between the tables.

2 Snowflake database

Snowflake database is a cloud-based data warehouse platform that provides a scalable, secure, and flexible solution for storing and processing large volumes of structured and semi-structured data. Snowflake database is not a data model, but rather a data warehouse architecture that uses a unique approach to separate the storage, compute, and services layers of the data warehouse. This means that you can store any type of data in Snowflake database without worrying about the schema, and you can adjust the compute resources according to your workload and performance requirements. You can also use Snowflake database to access and integrate data from various sources, such as files, streams, or external databases.

3 Cost comparison

The cost of a data warehouse depends on several factors, such as the amount of data, the frequency of data loading and querying, the complexity of the data transformations and analysis, and the type of service and pricing model you choose. Snowflake schema and snowflake database have different cost implications for your data warehouse project. Snowflake schema can reduce the storage cost of your data warehouse by eliminating data duplication and increasing data compression. However, snowflake schema can also increase the query cost of your data warehouse by requiring more joins and filters to access the data from multiple tables. Snowflake database can reduce the query cost of your data warehouse by allowing you to scale up or down the compute resources as needed, and by optimizing the query execution and caching. However, snowflake database can also increase the storage cost of your data warehouse by charging you for the amount of data you store and the number of times you access it.

4 Scalability comparison

The scalability of a data warehouse refers to its ability to handle increasing amounts of data and users without compromising the performance and reliability of the system. Snowflake schema and snowflake database have different scalability advantages and challenges for your data warehouse project. Snowflake schema can improve the scalability of your data warehouse by simplifying the data loading and maintenance processes, and by enabling faster data updates and changes. However, snowflake schema can also limit the scalability of your data warehouse by creating more complex and slower queries, and by requiring more coordination and synchronization between the tables. Snowflake database can improve the scalability of your data warehouse by providing unlimited storage capacity and elastic compute power, and by supporting concurrent and parallel queries and operations. However, snowflake database can also limit the scalability of your data warehouse by introducing more network latency and bandwidth consumption, and by requiring more security and governance measures.

5 How to choose

When deciding which data model or data warehouse platform is best for your project, there is no single answer as it depends on your specific data needs, goals, and constraints. Generally, snowflake schema is preferred for smaller and simpler data sets that require minimal storage costs. On the other hand, snowflake database is better for larger and more complex data sets that require optimized query performance and flexibility. For mixed or dynamic data sets, you may consider using a combination of snowflake schema and snowflake database depending on the type and purpose of the data to balance storage and query costs.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?