Data Partitioning vs Table Partitioning
First, we need to understand that Data Partitioning is different from Table Partitioning. Data Partitioning involves dividing the data we want to store into multiple tables. On the other hand, Table Partitioning is a system used in SQL to store data in such a way that when we query data with a filter, we don’t have to read the entire table. Instead, it uses the partitioned columns to select which rows to read from.
Main Benefits of Data Partitioning
- Scalability: When we divide data into sections, we can scale up the database system more easily.
- Performance: If we partition the data well, it can improve data loading speed. For example, it allows parallel data processing.
- Security: By separating sensitive from non-sensitive data, we can better control user permissions. For instance, we might store all customer data linked to a Customer ID in one table and store Customer ID to customer names in another table. This way, when analyzing data, the customer’s name might not be necessary.
Methods of Data Partitioning
- Horizontal Partitioning(also known as Sharding): This involves dividing data so that each table has the same schema. Each partition in this method is called a shard. For example, we might store customer data with names starting from A-M in one table and N-Z in another.
- Vertical Partitioning: This method divides data based on the pattern of use or frequency of use. For instance, product details like color, size, and product code might be in one table, while stock information is in another. An example of separating customer-sensitive data from non-sensitive data is vertical partitioning.
- Functional Partitioning: This involves dividing data based on the domain of use, such as Finance, Customer Service, Marketing, etc. This design ensures that data does not need to be fetched across unrelated systems.Source: Data Partitioning Best PracticesIf you need consultation on data partitioning, the data engineering team at Davoy will be happy to assist you. Feel free to contact us with the contact form here [Contact]
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