How many rows can a record type synchronized at time in Appian?
How many rows can a record type synchronized at time in Appian?
Answer
Data sync in Appian copies data from an external source, like a database, into Appian’s own data layer. Records then load and query faster, and you can use record relationships and record-level security.
How many rows a record type can sync depends on the environment’s capability tier:
- Standard: up to 4 million rows per record type
- Advanced: up to 20 million rows per record type
- Premium: no predefined limit
Example:
Say I’m building a telecom funding app where service providers submit funding requests, and the FundingRequest table has 6 million rows. With data sync turned on for that record type:
- On Standard, 6 million is over the 4 million cap. I’d add a sync filter so only active requests sync, not the full history.
- On Advanced, 6 million fits under 20 million, so the whole table can sync, though other platform constraints still apply.
- On Premium, there’s no row cap, but sync time and resource use still matter at that size.
If the app only works with active requests, I’d use the sync filter on any tier. If syncing doesn’t make sense at all, Direct Data Access queries the source database directly instead of keeping a copy in Appian.
For interviews: check the environment’s tier before syncing a large record type. Use a sync filter to skip data you don’t need, and switch to Direct Data Access when the volume or sync requirements make syncing a poor fit.
https://docs.appian.com/suite/help/26.7/about-data-sync.html
Check yourself
Question 1 of 4, on what the answer above covers.
1. Your environment is on the Standard tier. The `FundingRequest` table has 6 million rows, and the app only ever shows active requests. What's the best way to set up the record type?
2. A team on the Premium tier says, "There's no row limit, so we'll sync every table in full." What's the most useful response?
3. When does Direct Data Access make more sense than data sync?
4. In an interview you're asked how you'd approach syncing a very large record type. What should you do first?