Even if I’m a real advocate of Apps Script, I’m also very aware of its limits when it comes to performance.
When a script keeps fetching the same API data or repeatedly processes large spreadsheets, things slow down fast. Each execution feels heavier than the previous one, and you end up wasting both user time and valuable API quota.
Caching solves this problem by avoiding unnecessary work.
In this article, we’ll walk through what a cache actually is, how the Cache Service works in Apps Script, and the situations where it makes a real difference.
What’s a Cache?
A cache is simply a temporary storage area that keeps data ready to use.
Instead of computing something again or fetching it every time, you store the result once, and reuse it for a short period.
For example, imagine calling an external API that takes half a second to respond. If you cache the result for five minutes, the next calls come back instantly. The data isn’t stored forever, just long enough to avoid waste.
This principle is everywhere in tech: browsers, databases, CDNs… and Google Apps Script has its own version too.
What Is Cache Service in Apps Script?
The Cache Service in Google Apps Script gives you a small, fast place to store temporary data. It comes in three “scopes” depending on your use case:
- Data shared across all users of your script (
getScriptCache) - Data specific to the current user (
getUserCache) - Data linked to a particular document (
getDocumentCache)
It only stores strings, which means that objects need to be serialized (JSON.stringify). The storage is also limited in size and duration: up to 100 KB per key, and a lifetime of up to 6 hours.
It’s not meant to replace a database or a sheet, it’s meant to speed up your script by avoiding repetitive or heavy work.
When Should You Use It?
Speeding up repeated API calls
If your script fetches data from GitLab, Xero, or any third-party API, calling that API every time is unnecessary. The Cache Service is ideal for storing the latest response for a few minutes. Your script becomes faster, and you avoid hitting rate limits.
Avoiding expensive spreadsheet reads
Large spreadsheets can be slow to read. If you always transform the same data (for example: building a dropdown list, preparing a JSON structure, or filtering thousands of rows), caching the processed result saves a lot of execution time.
Making HTMLService UIs feel instant
Sidebars and web apps built with HTMLService often reload data each time they open. If that data doesn’t need to be fresh every second, keeping it in cache makes the UI load instantly and improves the user experience noticeably.
Storing lightweight temporary state
For short-lived information—like a user’s last selected filter or a temporary calculation—Cache Service is much faster than PropertiesService, and avoids writing into Sheets unnecessarily.
A Simple Way to Use Cache Service
You can create a small helper function that retrieves data from the cache when available, or stores it if missing:
/**
* Returns cached data or stores a fresh value if missing.
* @param {string} key
* @param {Function} computeFn Function that generates fresh data
* @param {number} ttlSeconds Cache duration in seconds
* @return {*} Cached or fresh data
*/
function getCached(key, computeFn, ttlSeconds = 300) {
const cache = CacheService.getScriptCache();
const cached = cache.get(key);
if (cached) return JSON.parse(cached);
const result = computeFn();
cache.put(key, JSON.stringify(result), ttlSeconds);
return result;
}And use it like this:
function getProjects() {
return getCached('gitlab_projects', () => {
const res = UrlFetchApp.fetch('https://api.example.com/projects');
return JSON.parse(res.getContentText());
});
}This approach is enough to dramatically speed up most Apps Script projects.
Final Thoughts
The Cache Service is small, simple, but incredibly effective if used well. It won’t store long-term data and it won’t replace a database, but for improving performance and reducing unnecessary work, it’s one of the easiest optimizations you can add to an Apps Script project.
If you want, I can help you write a second article with more advanced techniques: cache invalidation, dynamic keys, TTL strategies, and UI refresh patterns.