Drupal’s Cache API plays a central role in delivering performance at scale. It allows developers to store and reuse data across requests, reducing load on the database and speeding up response times. With the right strategy, caching can reduce database queries by as much as 95%, while keeping content accurate and dynamic through smart invalidation.
This article breaks down the key components of Drupal’s caching system, cache bins, tags, contexts, and max-age, and shows how they work together in real-world scenarios.
We’ll also walk through a practical example: fetching data from a third-party API, storing it with the Cache API, and managing its lifecycle using Drupal’s built-in tools. Whether you’re improving backend performance or fine-tuning user experience, the Cache API gives you precise control over how and when content is served.
Cache API fundamentals
Drupal’s Cache API provides a standardized mechanism to store, retrieve, and invalidate cached data. By abstracting the underlying storage system, you write the same code regardless of whether the data is stored in a database, memory, or even a remote backend like Redis.
Key principles of the cache API
Core Interfaces and Methods
Before diving into custom cache implementations, it is important to understand Drupal’s foundational interface: CacheBackendInterface. This interface lays out the standard methods for all caching backends in Drupal. It defines how cache items are stored, fetched, and invalidated. In essence, it’s the contract that every cache implementation must adhere to.
For more detailed technical reference, check out the official CacheBackendInterface documentation, which explains all the methods and recommended usage patterns.
Some of the key methods include:
Understanding these methods lays the groundwork for implementing effective caching strategies in your modules.
A Practical use case: caching third-party API data
To bring theory into practice, let’s consider a common scenario: retrieving weather information from a third-party API, caching the result, and ensuring that our cache is sensitive to changes by using cache tags, contexts, and max-age parameters.
Use case description
Imagine you have a module that fetches weather data from a public API. Because the API call is relatively expensive in terms of time and resources, you want to cache the results. However, the weather might change throughout the day, so you need to balance freshness with performance by setting an appropriate expiration (max-age) and associating cache tags so that when the weather information is updated (either manually or via another process), you can invalidate the cache selectively.
Sample implementation
Below is a sample implementation. This style is more in line with typical Drupal practices.
Explaining the flow
Cache metadata explained
Cache metadata is crucial in Drupal’s caching strategy. It controls how and when cached content should be invalidated.
Cache tags
Cache tags are string identifiers attached to cache entries. They track dependencies so that when a piece of content changes, related cache entries can be invalidated selectively. Consider this example:
Later, updating node 5 or the overall node list could trigger invalidation using these tags:
For more details on cache tags, refer to the official Drupal caching documentation.
Cache contexts
Cache contexts tell Drupal how the same cache entry might vary based on different runtime conditions (e.g., different users, URLs, or themes). When you build a render array, it might look like this:
Max-Age
The max-age setting defines the time period after which the cached data should be considered stale. For example:
Special values to note:
For a more in-depth discussion on cache metadata, please check the official Drupal caching API documentation.
Cache bins structure
Drupal organises cached data into separate “bins.” Each bin is a distinct storage container, designed to optimise different types of cache entries:
For example, using a specific bin may look like this:
Series navigation
This post is part of our comprehensive 10-part series on Drupal caching:
What’s next
Now that you’ve seen how Drupal’s Cache API works in practice, from understanding cache bins and metadata to implementing custom caching with third-party data, you’re ready to go a step deeper. In the next part of this series, we’ll shift focus to choosing the right cache backend for your Drupal site.
Different backends come with different trade-offs. Whether you're considering the default database cache, memory-based systems like Memcached or Redis, or cloud-managed solutions, the backend you choose directly affects cache hit rates, memory usage, and site responsiveness.
We’ll break down how each option works, when to use them, and how to configure them correctly in a production environment. Stay tuned as we continue building toward a complete understanding of caching in Drupal, one layer at a time.