Maintaining a Record of Change: Exploring Database Object Versioning Techniques

Imagine you manage a product database. Initially, each product might have only a name and price. Later, you decide to add a description and stock level. How would you implement this change without losing the existing data?

Solutions:

There are multiple approaches to versioning database objects:

Separate Versioning Table:

• Create a new table to store historical versions of your main table.
• This table would have additional columns for version number, timestamp, and potentially the modified data itself.

Example (simplified):

CREATE TABLE products (
  id INT PRIMARY KEY,
  name VARCHAR(255),
  price DECIMAL(10,2)
);

CREATE TABLE product_versions (
  id INT PRIMARY KEY,
  product_id INT REFERENCES products(id),
  version INT,
  created_at DATETIME,
  data JSON // Store modified data in JSON format
);

// Insert initial product data
INSERT INTO products (name, price) VALUES ('T-Shirt', 19.99);

// Update product with versioning
UPDATE products SET price = 24.99;
INSERT INTO product_versions (product_id, version, created_at, data)
SELECT id, 2, NOW(), JSON_BUILD_OBJECT('price', 24.99) FROM products;

Schema Versioning:

• Instead of separate tables, embed version information within your existing table.
• Add additional columns like "version" or "modified_at" to track changes.

ALTER TABLE products ADD COLUMN version INT DEFAULT 1;

// Update product with versioning
UPDATE products SET price = 24.99, version = version + 1;

Choosing the Right Approach:

• Separate table: Offers better isolation and easier querying historical data.
• Schema versioning: Simpler to implement but can become cumbersome with frequent changes, impacting performance.

Related Issues:

• Versioning overhead: Both approaches add complexity to your database and require additional maintenance.
• Data persistence: Decide how long to retain older versions and how to handle data deletion.
• Version conflict resolution: In collaborative environments, strategies are needed to manage potential conflicts when multiple users modify the same data concurrently.