With the growth of AI in data engineering, finding scalable ways to model your data has become more important. Modelling your data often involves choosing between star, snowflake, and galaxy schemas, each with its strengths and weaknesses.
The schema is the architectural blueprint for a well-organized, related, and stored dataset for analytical processing. The choice of schema impacts performance, scalability, and usability. The three widely adopted schemas are the Star, Snowflake, and Galaxy Schema. I’m breaking them down to help you choose the schema that best fits your data needs.
Star Schema
The Star Schema has a central fact table containing measurable events such as sales, revenue, or counts, surrounded by dimension tables describing those events, such as customer, product, or time. Dimension tables are denormalised, meaning all relevant attributes are stored in a single table, even if this leads to redundancy.
Advantages of Star Schema:
- Star schemas are simple to design, implement, and understand, making them accessible for both technical and non-technical teams.
- Great for simple queries due to fewer joins being required when accessing the data, compared to normalised models like snowflake schemas. This speeds up analytical queries and reporting.
- It adapts well to fit OLAP models.
Snowflake Schema:
The Snowflake Schema is an extension of the star schema. It further normalises dimension tables into multiple related sub-dimension tables (for example, splitting a “product” dimension into category, brand, and item tables), reducing redundancy and creating a more branching, snowflake-like structure.
Advantages of Snowflake Schema:
- Dimension normalization reduces data duplication, thereby saving storage.
- Updates and changes are easier to manage, as each piece of information is stored only once.
- It supports detailed and complex relationships within dimensions.
Galaxy Schema:
The Galaxy Schema contains multiple fact tables that share dimension tables, creating a multiple-linked star-schema structure. It is useful for modelling complex businesses with many interconnected processes, like sales and inventory, that share common dimensions.
Advantages of Galaxy Schema:
- It Handles Complexity will which is Ideal for large organizations with multiple business processes and complex analytical needs
- The Shared dimensions prevent duplication across fact tables reducing redundancy
- Supports enterprise-scale data warehouse environments
