Data is a crucial part of our life. Whether it is an organization or the individual level, every important task requires data in one form or another.
At the senior or high level of management, when there is a large depository of data, various concepts and methods are used to manage the same.
Star and snowflake schema are two important concepts that are associated with data warehousing or depository.
Key Takeaways
- Star schema uses denormalized data structures, resulting in fewer tables, while snowflake schema uses normalized data structures, leading to more tables.
- Star schema allows for faster query performance, whereas snowflake schema requires more complex joins, slowing down query performance.
- Star schema consumes more storage space due to data redundancy, while snowflake schema minimizes redundancy, saving storage space.
Star vs Snowflake Schema
In data warehousing, a star schema is a database structure in which data is organized around a core fact table and linked to several dimension tables. The snowflake schema is a variant of the star schema in which the dimension tables are normalized to decrease redundancy and increase performance.
Star schema is the organizational structure that is used for monitoring the database. It is used in business intelligence to measure the data.
This structure is called the term star because, at the centre, there would be space for the fact table, and the other small table is positioned as points of the star.
Each star has one fact table containing the data that need to be analyzed.
The snowflake schema is the extended form or the structure of the star schema. This database depository model is comprised of a dimension table, fact table, and sub-dimension table.
This model or structure is quite difficult to understand as it has a complex design with more foreign keys.
Comparison Table
| Parameters of Comparison | Star Schema | Snowflake Schema |
|---|---|---|
| What is it? | Star Schema is an organizational structure in which the information is represented by lookup and fact table and primarily are comprised of dimension and fact table | Snowflake Schema is a structure used in business intelligence that represent the data in a normalized manner |
| Type of Model | It has a top-down model | It has bottom-up model |
| Design | It has a simple design structure | It has a complex design structure |
| Complexity | Star schema is easy to understand with low query complexity | Snowflake schema is difficult to understand with comparatively higher query complexity |
| Foreign Key | It has comparatively less number of foreign keys | It has more number of the foreign keys |
| Disk Space | Star schema use more disk space | Snowflake schema use less disk space |
What is Star Schema?
Star schema is the concept that is majorly used for business intelligence, or in other words, and it plays a significant role in database depository management.
It is comprised of a fact and dimensional table that stores a large amount of data that needs to be analyzed or measured.
Basically, two types of information are stored in the fact table, and it includes the numeric value and attribute value related to the dimension.
The numeric value is the unique value that does not relate to any data stored in the table, while the attribute value is not directly involved in storing the data, they store the value in a foreign key.
The star schema is related to recording information that could be similar and result in duplicated data. It is designed in a simple way with easy data aggregation and integration.
This organizational structure provides fast access to the data and makes it easier and more convenient to evaluate the business insights. It works effectively with OLAP systems that consequently store data by creating OLAP cubes.
What is Snowflake Schema?
The snowflake schema is the structure that assists in maintaining and analyzing the data. It is comprised of a sub-dimension, dimension, and fact table.
This bottom-up model normalizes the data effectively by linking one reference table to another. The model resides in that of a snowflake as it contains the fact table at the centre, and the reference table constitutes the branches.
Snowflake schema has a complex design and is a bit difficult to maintain.
Main Differences Between Star and Snowflake Schema
- Star Schema is an organizational structure in which a lookup and fact table represents the information and primarily are comprised of dimension and fact table. On the contrary, Snowflake Schema is a structure used in business intelligence that represents the data in a normalized manner.
- Business intelligence uses various organizational structures for analyzing the data. Star schema is based on the top-down model. In contrast, the snowflake schema on the other side is based on the bottom-up model.
- The data stored in various formats constitute the data warehouse. The multidimensional models are designed to derive various queries from the data depository. Star schema has a simple design structure, while snowflake schema on the other side has a complex design.
- Every business intelligence model which is designed for database warehouses has some complexity level that varies from one to another. Star schema is easy to understand with low query complexity. While snowflake schema, on the other side, is difficult to understand with comparatively higher query complexity.
- The star schema is designed in such a way that there would be no link or branching from any dimension table. But in the snowflake schema, one branch may associate with another one in one way or another.
Reference
- https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.5519
- https://dl.acm.org/doi/abs/10.1145/974121.974136
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This article is a valuable resource for information on star and snowflake schema. It is very comprehensive and informative.
I appreciate the thorough comparison between star and snowflake schema. The article was very comprehensive.
This article is a great intro to the basics of star and snowflake schema, ideal for those who are starting to delve into data warehousing. It’s a clear and concise explanation.
Agreed! This was a very informative read. Looking forward to more content on this topic.
I wholeheartedly agree. I particularly appreciate the comparison table which succinctly outlines the differences.
The article provides an insightful analysis of star and snowflake schema. It gives the reader a clear understanding of their differences and functionality.
Absolutely, it serves as an excellent resource for those with an interest in data warehousing and database management.
I found this article to be lacking in addressing the practical applications of star and snowflake schema. Real-world examples would have been beneficial.
I respectfully disagree. The focus was on explaining the concepts, not providing practical applications. It’s important to understand the theory before delving into specific use cases.
This article has shed light on the differences between star and snowflake schema. It was an intellectually stimulating read.