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Database (DB) Caching and DB Tertiary Caching
Category: Databases
Normalization in Relational Databases
This is a continuation of my posts on relational databases, started here. Previous posts on this theme, “Data Modeling“, “Let’s Talk About Database Schema“, “The Exasperating Topic of Database Indexes“, “The Keys & Relationships of Relational Databases“, and “Relational Database Query Optimization“.
Consider you’re a die-hard fan of progressive death metal, with a particular affinity for bands like Allegaeon. Over the years, you’ve accumulated a vast collection of CDs, vinyls, and other memorabilia.
Your collection has grown so much that you decide to document every item meticulously. Each piece of memorabilia contains information about the album, track titles, band members, and so forth. If you scribbled down every detail in one continuous list, you’d end up with a lot of repeated information. For instance, both “Proponent for Sentience” and “Formshifter” would mention the same band members like Riley McShane and Michael Stancel.
Normalization is akin to setting up separate lists or sections in your documentation. One section purely for “Band Members” where you detail members of Allegaeon over time. Another section for “Albums”, where instead of listing band members all over again, you simply refer back to the “Band Members” section. This kind of organization cuts down redundancy and ensures if, say, a band member leaves, you have only one spot to update.
Continue reading “Normalization in Relational Databases”Relational Database Query Optimization
This is a continuation of my posts on relational databases, started here. Previous posts on this theme, “Data Modeling“, “Let’s Talk About Database Schema“, “The Exasperating Topic of Database Indexes“, and “The Keys & Relationships of Relational Databases“.
Query optimization refers to the process of selecting the most efficient way to execute a SQL query. The goal is to retrieve the requested data as quickly and efficiently as possible, making the best use of system resources. Given that there can be multiple strategies to retrieve the same set of data, the optimizer’s role is to choose the best one based on factors like data distribution, statistics, and available resources.
Query Optimizers
Continue reading “Relational Database Query Optimization”The Keys & Relationships of Relational Databases
This is a continuation of my posts on relational databases, started here. Previous posts on this theme, “Designing a Relational Database – Data Modeling, “Let’s Talk About Database Schema“, and “The Exasperating Topic of Database Indexes“.
In the context of relational databases, “keys” and “relationships” are fundamental concepts that help in ensuring data integrity, organizing data efficiently, and enabling meaningful data retrieval. Let’s break these down:
1. Keys
A key is an attribute (or a set of attributes) that uniquely identifies a record in a table. Various types of keys exist in relational databases:
- Primary Key: This uniquely identifies each record in a table. A primary key cannot have NULL values, and each value must be unique. A table can have only one primary key, which may consist of single or multiple columns.
- Foreign Key: This is an attribute or set of attributes in a table that refers to the primary key in another table. It establishes a relationship between two tables. A foreign key ensures records in one table correspond to records in another.
- Unique Key: Similar to a primary key, it uniquely identifies each record in the table. The difference is that a table can have more than one unique key, but only one primary key. Unique keys can have NULL values, but the values must be unique.
- Composite Key: When more than one attribute is used to uniquely identify a record in the table, such a key is called a composite key.
- Candidate Key: Any attribute or set of attributes that could serve as the primary key is a candidate key. It means it can uniquely identify records in the table.
- Super Key: It is a set of attributes that, when taken collectively, can be used to uniquely identify records. A super key can have additional attributes that are not strictly necessary for unique identification.
2. Relationships
Relationships in relational databases determine how tables connect to one another and how data correlates:
- One-to-One (1:1) Relationship: In this relationship, one record in a table is related to one and only one record in another table. For instance, each employee in a company might have one unique work ID.
- One-to-Many (1:N) or Many-to-One (N:1) Relationship: One record in a table can be related to one or more records in another table. For example, one customer can place many orders, but each order is made by one customer.
- Many-to-Many (M:N) Relationship: Multiple records in one table are related to multiple records in another table. For instance, students and courses. One student can enroll in many courses, and one course can have many students. This relationship is typically resolved in relational databases using a junction table (or bridge table).
Relationships are typically enforced using Foreign Keys. When a foreign key in one table refers to the primary key of another, it creates a linkage that ensures the validity of the data and maintains referential integrity.
Continue reading “The Keys & Relationships of Relational Databases”The Exasperating Topic of Database Indexes
Previous posts on this theme, “Designing a Relational Database – Data Modeling“ and “Let’s Talk About Database Schema“.
Indexes aren’t necessary right? Of course not, they’re just peripherally superficial things that sit like leaches on a database table’s column!
Ok, bad database satire aside, let’s get real. Indexes are extremely useful for a plethora of reasons. They play a crucial role in optimizing the speed of database operations, especially retrieval operations.
Demystifying the Magic Behind Relational Database Indexes
Ever tried finding a specific recipe in a massive cookbook? Imagine if there wasn’t an index! Just as that cookbook index saves you hours of flipping through page after page, a relational database index works wonders by helping the system quickly locate rows within a table without the tedious process of examining each one.
So, How Does This Magic Work?
Continue reading “The Exasperating Topic of Database Indexes”
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