Best Ruby on Rails Database Optimization Techniques to Boost Performance

To discuss database optimization, we first need to understand databases, how to manage them, and why and when Ruby on Rails database optimization is necessary. 

A database is an organized collection of structured information—that’s it! However, to interact with this collection of structured information, you need to use a management system. A database is usually controlled by a database management system (DBMS), which is software that controls the storage, organization, and retrieval of data.

Here are DBMS examples:

• MySQL is one of the most popular open-source SQL database management systems developed, distributed, and supported by Oracle Corporation.

• PostgreSQL is a powerful, open-source object-relational database system with over 35 years of active development, which has earned it a strong reputation for reliability, feature robustness, and performance.

• MongoDB is an open-source, nonrelational database management system (DBMS) that processes and stores various forms of data using flexible documents instead of tables and rows.

• Amazon RDS is an easy-to-manage relational database service. It is simple to set up, operate, and scale with demand.

As we know how to store our data, we should know how to manipulate it and extract it from our database—this is what SQL is used for.

A DBMS is a system designed to store, retrieve, and manage data, while SQL (Structured Query Language) is the tool used to interact with the data within the DBMS. These two work closely together: when you store data in a DBMS and need to access or modify it, SQL is the language you'll use.

As someone already stated, with great power comes… slowness of queries. Yes, exactly. Active Record has many advantages and capabilities that, if used incorrectly, can become disadvantageous. Modern web applications are data-driven ecosystems where database efficiency isn't just a technical nicety—it's a fundamental business requirement. As user bases grow and data volumes expand, Ruby on Rails applications can quickly get stuck by inefficient queries, slow database interactions, and unnecessary overhead. A single poorly optimized database query can transform a responsive application into a frustratingly slow experience. 

Optimizing SQL queries in Rails applications is critically important and can significantly impact your application's performance, scalability, and user experience. Database optimization is not just a technical task but a strategic approach to building robust, scalable Ruby on Rails applications.

Source: Linkedin

The Active Record is the Rails ORM (Object Relational Mapping) tool, which implements the Active Record architectural pattern, which Martin Fowler describes in the book Patterns of Enterprise Application Architecture as "an object that wraps a row in a database table, encapsulates the database access, and adds domain logic to that data."

Source: Martin Fowler

As I mentioned earlier, ActiveRecord is Rails ORM, but what is ORM and what is it used for? Object-Relational Mapping (ORM) is a method that enables working with database data in an object-oriented world. The term "ORM" usually refers to a library designed to implement this approach. ORM frameworks bridge the gap between databases and object-oriented programming by mapping tables to classes and rows to objects. This allows developers to interact with the database using objects instead of raw SQL queries, which greatly increases the maintainability of the code. Having a basic idea of what Active Record is, let’s look at its key features.

Active Record offers a rich set of features that improve the interaction between an application and its database:

• Convention over Configuration. The Active Record minimizes the need for explicit configuration by following conventions. For instance, it assumes that a model named User corresponds to a database table named Users, and its primary key is ID by default.

• Associations. Defining relationships between models is much easier since Active Record provides macros such as belongs_to, has_many, and has_one, which facilitate managing associated data.

• Query Interface. Active Record provides methods to query data using Ruby syntax instead of raw SQL; methods like where, find, and order allow for easy and readable queries.

• Validations. Active Record comes with built-in validation helpers, which help ensure data integrity before saving records to the database.

As you can see, Active Record simplifies database interactions with features like intuitive conventions, associations, a query interface, and validations, enabling efficient management of application data.

Query tuning in Ruby on Rails optimizes database queries to improve application performance and reduce unnecessary database load. There are several key strategies used for Rails performance tuning. One of the techniques is eager loading. Eager loading in Ruby on Rails is used to optimize database queries by reducing the number of queries made when accessing associated records. In essence, it allows you to load associated records in a single or fewer database queries, preventing the notorious N+1 query problem.

The N+1 query problem is a typical performance issue when working with ActiveRecord. The N+1 query problem arises when we try to query a parent object (e.g., posts) and then make an additional query for each related child object (e.g., comments) individually. This inefficiency can significantly slow down performance since it’s better to make one bigger query that returns 100 results than 100 queries that each return 1 result. Solutions to this would be to use methods like includes or joins to preload associated records and reduce the number of queries.

Ruby# Bad
@posts = Post.all
@posts.each do |post|
  post.comments.map(&:text)
end

# Good
@posts = Post.includes(:comments).all
@posts.each do |post|
  post.comments.map(&:text)
end

The Bullet Gem can help you monitor your queries during development and alert you when to add eager loading to address N+1 queries. To learn more about the Bullet Gem, read this article: 5 Must-Have Ruby on Rails Gems You Can’t Miss in 2024. 

Eager loading is a powerful technique in Ruby on Rails for optimizing database queries and preventing performance bottlenecks. By understanding and correctly implementing eager loading, you can significantly improve the efficiency of your Rails applications, especially when dealing with complex data relationships. Remember, the key is to load only what you need, when you need it, and to do so in the most efficient manner possible.

Indexing is a database optimization technique that speeds up query execution by creating a data structure to locate rows quickly based on the values in specific columns. When talking about Ruby on Rails database indexing in practice, you can add indexes through migrations using the add_index method, especially on frequently queried fields like foreign keys or unique identifiers, to improve read performance. However, indexing may not be useful in cases where most of the data in a single column is the same.

Rubydef change
  add_index :users, :email, unique: true
end

Database Views are virtual tables created by saving the result of a SQL query as a reusable object within the database. They allow developers to encapsulate complex or frequently used queries, enabling more straightforward and more efficient access to aggregated or transformed data. Database Views are beneficial for abstracting business logic into the database layer, improving consistency, and reducing duplication of query logic across an application.

Ruby CREATE OR REPLACE VIEW simplified_posts AS
    SELECT id, body
    FROM posts;
SQL

Caching temporarily stores frequently accessed data to reduce redundant queries and improve performance. It can be implemented using low-level caching. This reduces database load and speeds up response times. However, there might be better use cases than caching when data changes frequently, and the latest changes should be displayed to the user immediately.

RubyRails.cache.fetch("expensive_query", expires_in: 12.hours) do
 Posts.where(published: true)
end

When working with large datasets, processing records in small batches prevents memory overload and improves efficiency. Rails provides methods like find_in_batches to load and process records in chunks, avoiding loading an entire table into memory simultaneously.

RubyPost.find_in_batches(batch_size: 500) do |posts_batch|
 posts_batch.each do |post|
   post.update!(published: false)
 end
end

Bulk operations refer to executing multiple database operations in a single action, which can significantly improve performance by reducing the number of database queries. Instead of executing individual operations one by one (which can be slow and inefficient), bulk operations group similar actions together, minimizing the overhead of database communication. But note that bulk operations omit callbacks!

RubyPost.insert_all(
 [
   {title: "Title 1", body: "Text 1"},
   {title: "Title 2", body: "Text 2"}
 ]
)

Selective column retrieval minimizes memory usage and boosts performance by querying only the required columns instead of the entire row. In Rails, the select method lets you specify columns to retrieve, reducing the data fetched from the database. But use it wisely because in some cases, you may want to use lazy loading.

RubyPost.where(published: true).select(:title)

As you can see, there are many cases and places that, if mishandled, can lead to performance deterioration. I encourage you to check out the book Ruby Performance Optimization by Alexander Dymo to learn more about possible performance improvements. However, it is sometimes necessary to go a level higher than queries and perform database scalability measures for optimization.

Scaling databases involves adjusting their architecture to handle increasing data and users. This can be done through vertical scaling, where existing hardware is upgraded, or horizontal scaling, which involves adding more servers to distribute the load. Additionally, there are plenty of strategies, such as sharding and replication, which, when adequately adapted, can play a crucial role in maintaining database performance.

Source: CloudZero

Database Sharding

Sharding is a method of distributing data across multiple databases or servers to improve scalability and performance. Each "shard" holds a subset of the data, and a sharding strategy determines how data is partitioned, such as by location, user ID, or other criteria. This approach helps handle high traffic loads by balancing the data across many servers.

Partitioning

Database partitioning involves splitting an extensive database into smaller, more manageable pieces called partitions. Partitioning differs from sharding in that we deal with a single database instance while sharding divides shards into multiple database instances.

Data Replication

Data replication is copying and maintaining database objects, such as tables or entire databases, across multiple servers. The goal is to increase data availability and fault tolerance by ensuring that copies of the data are available for read and write operations.

CAP Theorem

The CAP Theorem states that a distributed data store can achieve at most two of three properties: Consistency, Availability, and Partition Tolerance. Consistency ensures that all nodes in the system have the same data, Availability ensures that the system remains operational even if a node fails, and Partition Tolerance ensures that the system can handle network failures. In practice, systems must prioritize two properties based on their needs and trade-offs.

Active Record is a powerful tool in Ruby on Rails that simplifies database interactions by mapping tables to objects. However, achieving optimal performance in Ruby on Rails applications requires consistent focus on database optimization and ActiveRecord performance tuning. By combining techniques like indexing, eager loading, and caching, developers can ensure that Rails applications remain fast and scalable, even under substantial data loads .While Active Record accelerates development, maintaining performance is critical. Ruby on Rails is a fantastic framework for building scalable web applications. With the right optimizations and advanced database scaling strategies like sharding partitioning, and replication, large-scale data can be efficiently managed and ensure long-term success.