Last weekend, I explored a topic that really interests me: how Bubble performs efficient searches in its database. In this article, we’ll discuss data indexing and how it can make database queries faster and more optimized.
1- How Searches Work in Bubble’s Database
Before we dive into indexing, we need to understand how searches work in a database. Simply put, database searches allow Bubble to retrieve data and use it within your app, whether to populate a repeating group, table, or list.
These searches are built using dynamic expressions. This flexibility allows you to configure and search for almost any data needed to make your app function smoothly. However, this freedom also means that you might set up searches that are not optimized for performance and workload units (WU) consumption.
How is WU Consumption Calculated?
Imagine that, for every item stored or action performed in the database, there is a cost in workload units (WU), depending on the data volume involved. Actions like “Make changes to a list of things” may cost more WU than lighter actions, like “Scroll to element.”
Factors Affecting WU Consumption in Searches
- Volume of Data Returned by the Database:
- Complexity of Dynamic Expressions:
What is Search Complexity?
Search complexity is a concept that covers the time and effort required for Bubble to identify records that meet specific constraints. Simply put, a database search filters out records that don’t match the set constraints. For example, if the database has 100,000 records and only 20,000 meet the criteria, Bubble quickly removes irrelevant records, making the search faster.
This process becomes even more efficient with data indexing. Indexing allows the database to organize data in a way that makes it quicker to locate the required records. For example, if your app frequently searches for products by price, indexing allows the database to sort these products by value, speeding up the exclusion of records outside the desired range.
How Does Indexing Work in Bubble?
Indexing is an automatic process in the database that occurs only when the data volume justifies it. Bubble identifies when the database needs to be indexed to improve query performance. Indexing enables complex searches that would otherwise require more time and resources to be completed faster without impacting WU consumption.
Best Practices for Optimizing Searches in Bubble
To maximize search efficiency in your Bubble app, here are some practical tips:
- Filter data directly in the database whenever possible: Instead of loading all data and filtering on the frontend, use filters directly in the query to reduce the data volume loaded.
- Avoid complex searches whenever possible: Limit the number of filters and dynamic calculations in a single query.
- Use repeating groups thoughtfully: Repeating groups are useful, but they can cause a WU overload if they load many records at once.
- Analyze each field’s usage in your data: Avoid storing excessive information in long text fields, especially when they are frequently accessed in searches.
- Monitor WU consumption: Regularly check workload unit consumption and optimize queries as needed to keep your app’s costs under control.
This knowledge about indexing and optimization in Bubble is essential to make your app more efficient and cost-effective. By applying best practices and understanding database limitations, you can ensure that your app’s performance is optimized, providing a smoother and more responsive user experience.