How to Optimize Multilingual Database Structure for Efficient Storage and Retrieval?

Multilingual Database Structure Optimization

This question explores the optimal database structure for storing multilingual data while avoiding the need for table modifications or data duplication. Three approaches are presented:

Approach 1:

This approach combines data into a single table with language-specific columns, such as:

[ products ]
id (INT)
name-en_us (VARCHAR)
name-es_es (VARCHAR)
name-pt_br (VARCHAR)
description-en_us (VARCHAR)
description-es_es (VARCHAR)
description-pt_br (VARCHAR)
price (DECIMAL)

Limitations: Requires table modification for each new language added.

Approach 2:

This approach creates separate tables for each language, such as:

[ products-en_us ]
id (INT)
name (VARCHAR)
description (VARCHAR)
price (DECIMAL)

[ products-es_es ]
id (INT)
name (VARCHAR)
description (VARCHAR)
price (DECIMAL)

Limitations: Duplicated price field in each language table. Requires creation of new tables for each new language.

Approach 3 (Recommended):

This approach uses a neutral table with a separate translated table with a structure like:

[languages]
id (INT PK)
code (VARCHAR)

[products]
id (INT PK)
neutral_fields (MIXED)

[products_t]
id (INT FK, PK)
language (INT FK, PK)
translated_fields (MIXED)

Advantages:

• Avoids table modifications: No need to modify the table structure for new languages.
• Eliminates data duplication: The price field is stored only once in the neutral table.
• Performance: Retrieving multilingual data is efficient using a single LEFT JOIN.

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