Basic Example
Input 1
Input 2
Result (Union)
How it works
1
Connect two inputs
Drag two data streams into the Union node. These can come from any upstream nodes in your workflow.2
3
Configure dedup settings (optional)
When using Distinct mode, configure which fields define uniqueness and which input wins on duplicates.Dedup Key - select which fields from each input correspond to each other. These field pairs define uniqueness for deduplication. You can add multiple fields for a composite key (e.g.,ID + Date).Priority - when duplicates are found, controls which input’s row is kept.
Field mappings are required when using Distinct mode. In All mode they are optional - rows are simply stacked.
Output
The Union node produces a single output stream containing the combined rows from both inputs. The output is available as an input to any downstream node in your workflow.Example with Deduplication
Input 1
Input 2
Configuration: Distinct, Dedup Key:
ID, Priority: Input 1 wins
Result:
All vs Distinct
When using All, if both tables contain the same record, the result will include it twice:
When using Distinct, duplicates are removed based on the dedup key, keeping only one row per unique combination.
Union vs Merge vs Bond
Best Practices
- Ensure inputs have compatible schemas (same fields and meaning)
- Use All when you want full data coverage and duplicates are acceptable
- Use Distinct when you need a clean dataset and duplicate records must be removed
- Carefully define dedup keys and priority rules
Common Pitfalls
- Mismatched columns - same name but different meaning across inputs
- Missing dedup key - leads to incorrect duplicate removal
- Over-aggressive deduplication - can cause data loss
Related Nodes
- Merge Node - joins two datasets side-by-side rather than stacking vertically
- Bond Node - creates logical relationships between entities