Hi @Big_Cat_Public_Safety_Act,
As noted in earlier replies, this seems related to some of your other discussion topics although you have extra questions here.
Scalability and feasibility will depend on many factors including your schema design, application design, indexes, deployment resources, workload, performance expectations, and funding. The best way to estimate would be generating some data and workload in a representative test environment.
There are different dimensions to scaling (performance scale, cluster scale, data scale) and you can see some examples at Do Things Big with MongoDB at Scale.
As @Nick notes, Twitter and Facebook weren’t built from the start to handle the user base they have today. Both have evolved into very large application platforms and companies with 1000s of engineers and millions or billions of users.
As per #1, any estimate is going to depend on many factors and this question isn’t directly answerable. The estimated number of users will also vary depending on what those users are doing, and when. An application with 10,000 daily users distributed globally could mean anywhere from 10s to 100s or 1000s of concurrent users depending on session durations, time zones, and how they interact with your app.
I recommend reviewing the MongoDB Schema Design Patterns to see which might apply to your application and use cases.
For example, the Attribute Pattern would be helpful for the variety of fields you are planning, including unpredictable field names.
If you have more ambitious search requirements, Atlas Search has a rich set of search features and operators.
If you are looking to optimise some specific use cases, I suggest starting a discussion with more concrete details including example documents with your proposed schema, common queries, and any concerns or findings you have so far.
Regards,
Stennie