Relational Database
A database is one of the most brittle and critical components of any system. Understanding how it works is crucial; the better you know your database, the easier it becomes to solve 50-60% of system-related problems.
In a relational database, data is organized into tables, with rows and columns, making it ideal for transactional systems that require structured data and complex queries.
Key properties of relational databases include:
Data Consistency: Ensures the data remains accurate and valid throughout its lifecycle.
Data Durability: Guarantees that once data is saved, it will remain intact even in the event of a system crash.
Data Integrity: Maintains correctness using rules and relationships, preventing invalid or corrupt data.
Constraints: Rules like primary keys, foreign keys, and unique constraints ensure data validity and enforce relationships.
Everything in One Place: Centralized data storage simplifies management and reduces redundancy.
ACID Properties
Relational databases follow ACID principles to ensure reliable transactions.
Atomicity:
A transaction consists of one or more operations, and either all succeed or none do.
For example, if a transaction involves updating two tables and one operation fails, the database will roll back all changes to avoid inconsistent data.
Consistency:
Ensures that the database remains in a valid state before and after a transaction.
Constraints like primary keys, foreign keys, and validations help maintain consistency.
Tools like cascade and triggers play a role:
Cascade: Automatically updates or deletes dependent data. For example, if a parent record is deleted, associated child records are also removed.
Triggers: User-defined functions that execute automatically in response to specific changes, enabling automated processes like logging or additional data updates.
Durability:
Once a transaction is committed, the changes are permanently saved to disk, ensuring the data will not be lost, even in case of a failure.
Relational databases guarantee durability by writing the changes to disk before marking the transaction as complete.
Isolation:
Controls the visibility of data between parallel transactions to prevent conflicts.
For instance, if two users are updating the same record simultaneously, isolation ensures that they do not interfere with each other, maintaining consistency.
Practical implementations may involve repeated checks rather than strict isolation to optimize performance in less-critical scenarios.
Why Relational Databases?
Relational databases offer strong guarantees for data consistency, durability, and correctness, making them the backbone of transactional systems. Their ability to enforce complex relationships and rules ensures reliability, scalability, and fault tolerance, essential for building robust systems.