Optimizing and scaling Firebase for improved performance

Is it possible to efficiently retrieve schedules from a database with thousands, or even millions, of records in the future?

I am planning on storing schedules from healthcare professionals in a collection, but I am unsure if it is better to store them within the professional's entity or within the unit itself.

While Firebase allows for the creation of indexes, I am concerned about retrieving schedules in a simple manner.

1. Initial Approach:

db.collection('unity').doc('6BfbptQ8blacBLi1GNIJ').collection('schedules').

2. Alternative Approach:

 db.collection('unity').doc('6BfbptQ8blacBLi1GNIJ')
.collection('professionals').
doc('Z6JDd0Ek7WO8yqiZJkBuJooF1FH3')
.collection('schedules').

The second way would require traversing through all professionals in the unit to gather their schedules and aggregating the counts, which might not be optimal.

I am curious about the performance implications when dealing with collections containing thousands or millions of records.

angulartypescriptfirebasegoogle-cloud-firestore

Answer №1

The success of transferring data depends greatly on the amount of information being processed. While handling thousands of documents may seem manageable, one must consider the potential costs associated with network transfer and memory storage on the client device. It is important to take into account the amount of data being moved and the time it will take to complete the transfer.

Without a clear understanding of the specific query results, network capabilities, and available memory resources, it is difficult to determine if this process will be successful. Performing your own benchmarks is recommended for accurate evaluation.

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