Should I Store Lists in a Single SQL Column or Normalize My Data for Faster Queries?

Managing "List" Entries in SQL Tables: Queries vs. Normalized Data

When working with SQL tables, it's common to store data in either a single row with a "list" entry or a separate row for each entry. This question examines which approach is more efficient in terms of query time for a specific use case.

Current Approach with "List" Entry

The questioner has an existing SQLite table with rows resembling:

value, "a,b,c,d,e,f,g,h,i,j", value3, value4

where queries search for pairings of "value" and "%b%" using the LIKE operator.

Proposed Approach with Normalized Data

To improve query efficiency, the poster proposes creating a new table where each row represents a permutation:

value, a, value3, value4
...
value, j, value3, value4

Queries would then use the "=" operator to search for "value" and "b."

Benefits of Normalization

The answer to this question strongly recommends using a normalized table structure. This is because LIKE '%something%' queries cannot utilize indexes, resulting in slower lookup times. Additionally, using a "list" column in an RDBMS goes against best practices.

Normalization Benefits Include:

• faster queries using indexes
• elimination of the "CSV" column anti-pattern
• improved data integrity and flexibility

By normalizing the data, you can further enhance performance by removing duplicate entries and creating relationships between tables, allowing for more complex and efficient queries.

The above is the detailed content of Should I Store Lists in a Single SQL Column or Normalize My Data for Faster Queries?. For more information, please follow other related articles on the PHP Chinese website!