n8n Merge and Aggregate Nodes: How to Combine Data from Multiple Sources (2025)
Real automations rarely pull from one source. You're joining CRM records with enrichment data, combining rows from several sheets, or rolling many items into one summary. The Merge and Aggregate nodes are how you do that in n8n — and knowing which to reach for saves hours of confusion. Here's the practical breakdown.
Merge vs Aggregate: which problem are you solving?
These two nodes get confused constantly because both 'combine' data, but they solve opposite problems. Use Merge when you have two separate streams of items and want to bring them together — like matching customers from one source with orders from another.
Use Aggregate when you have many items in one stream and want to roll them into fewer — like turning 50 individual sales rows into a single item with a total, or collecting all email addresses into one list. Merge joins across branches; Aggregate condenses within a branch. Fix that distinction in your head and half the confusion disappears.
The Merge node modes, explained
The Merge node offers a few modes, and picking the right one matters. Append simply stacks the items from both inputs into one list — useful when you just want everything together regardless of matching. Combine by matching fields is the true join: it pairs items from input 1 and input 2 where a key (say, email or ID) matches, like a database join.
Combine by position zips the two inputs together item-by-item based on order, which is handy when you know both streams are aligned. The most common real-world use is 'combine by matching fields' — enriching a base record with data fetched from a second source using a shared key.
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Aggregate and real-world patterns
The Aggregate node shines when you need a summary. Point it at a stream of items and it can collect a single field into a list, or combine everything into one item you can then total, count, or format. This is the node behind 'build me a daily digest' or 'sum today's orders' workflows.
A classic full pattern: pull data from several sources, Merge them on a common key to build complete records, then Aggregate the result into a single summary item that an AI node turns into a readable report. That combination — join the sources, condense the result, narrate it — is the backbone of most automated reporting in n8n.
Final thoughts
Combining data cleanly is a core automation skill: reach for Merge to join separate streams and Aggregate to condense one stream. Master those two nodes and you can wire together almost any set of sources into a single, useful output.
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