Understanding SYSTEM-VERSIONED and APPLICATION-VERSIONED Temporal Tables in MySQL: Exploring the Power of Historical Data Tracking

Introduction

Temporal tables in MySQL offer a powerful solution for tracking historical changes to data, providing valuable insights into how records have evolved over time. With the introduction of SYSTEM-VERSIONED and APPLICATION-VERSIONED temporal tables, MySQL has enhanced its capabilities to manage temporal data effectively. In this blog, we will dive into the internals of these temporal tables, exploring their implementation, use cases, and advantages. Understanding these features will empower database administrators and developers to make informed decisions when dealing with historical data, ensuring data integrity and historical accuracy.

Temporal tables in MySQL are a feature that allows you to maintain historical versions of data, enabling you to track changes to the data over time. There are two types of temporal tables in MySQL: SYSTEM-VERSIONED and APPLICATION-VERSIONED temporal tables.

  1. SYSTEM-VERSIONED Temporal Tables:
    • SYSTEM-VERSIONED temporal tables are managed entirely by the MySQL server, and they automatically maintain historical versions of data in a separate history table.
    • When you create a SYSTEM-VERSIONED temporal table, you define two tables: the current data table and the history table.
    • The current data table contains the most recent version of the data, while the history table stores all previous versions of the data, along with the timestamps indicating when each change occurred.
    • When you update a row in the current data table, the MySQL server automatically inserts the old version of the row into the history table, along with the timestamp of the change.
    • Similarly, when you delete a row from the current data table, the MySQL server marks the row as deleted in the current table and inserts a copy of the row into the history table, preserving the deleted version.
    • Retrieving historical data from a SYSTEM-VERSIONED temporal table involves querying both the current data table and the history table, using the appropriate timestamp criteria to get the desired version of the data.
  2. APPLICATION-VERSIONED Temporal Tables:
    • APPLICATION-VERSIONED temporal tables allow you to manage historical versions of data manually. Unlike SYSTEM-VERSIONED tables, there is no separate history table managed by the MySQL server.
    • When you create an APPLICATION-VERSIONED temporal table, you need to include two timestamp columns in the table definition: one for the valid time and one for the transaction time.
    • The valid time represents the period during which the data is considered valid, while the transaction time represents the time when the data was inserted or updated.
    • Unlike SYSTEM-VERSIONED tables, the management of historical data in APPLICATION-VERSIONED tables is done explicitly by the application. When a row is updated, it is up to the application to decide how to handle the previous version of the data, whether to store it in a separate table or archive it in some other way.
    • Similarly, when querying historical data from an APPLICATION-VERSIONED table, the application needs to consider both the valid time and transaction time columns to retrieve the appropriate version of the data.

In summary, SYSTEM-VERSIONED temporal tables in MySQL automatically manage historical versions of data in a separate history table, while APPLICATION-VERSIONED temporal tables require manual handling of historical data by the application. Both types of temporal tables are useful for scenarios where you need to track changes to data over time and maintain a historical record of the data for auditing, compliance, or historical analysis purposes.

Conclusion

Temporal tables in MySQL, including SYSTEM-VERSIONED and APPLICATION-VERSIONED variants, open up a new realm of possibilities for managing historical data. The ability to automatically track and manage changes over time allows organizations to gain deeper insights, audit data modifications, and meet compliance requirements effectively. By harnessing the power of these temporal tables, database administrators and developers can design more robust applications, safeguard data integrity, and ensure historical accuracy. Embracing temporal tables as part of a comprehensive data management strategy will undoubtedly pave the way for more data-driven and reliable systems, driving growth and success for businesses in today’s data-driven world.

About Shiv Iyer 444 Articles
Open Source Database Systems Engineer with a deep understanding of Optimizer Internals, Performance Engineering, Scalability and Data SRE. Shiv currently is the Founder, Investor, Board Member and CEO of multiple Database Systems Infrastructure Operations companies in the Transaction Processing Computing and ColumnStores ecosystem. He is also a frequent speaker in open source software conferences globally.