Google Sheets to Postgres, data stays consistent
Your “source of truth” lives in Google Sheets… until it doesn’t. A column gets renamed, someone pastes values over formulas, and now the Postgres table you rely on is quietly out of date.
This Sheets Postgres sync problem hits RevOps and Marketing Ops first, because reporting breaks fast. But founders feel it too when dashboards don’t match what the team sees in the spreadsheet.
This n8n workflow keeps Google Sheets aligned with Postgres on a schedule. You’ll see how it compares datasets, inserts new rows, and updates changed records so your database stays reliable.
How This Automation Works
The full n8n workflow, from trigger to final output:
n8n Workflow Template: Google Sheets to Postgres, data stays consistent
flowchart LR
subgraph sg0["Schedule Flow"]
direction LR
n0@{ icon: "mdi:play-circle", form: "rounded", label: "Schedule Trigger", pos: "b", h: 48 }
n1["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/compare.svg' width='40' height='40' /></div><br/>Compare Datasets"]
n2@{ icon: "mdi:swap-vertical", form: "rounded", label: "Split Out Relevant Fields", pos: "b", h: 48 }
n3@{ icon: "mdi:database", form: "rounded", label: "Retrieve Sheets Data", pos: "b", h: 48 }
n4["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/postgres.svg' width='40' height='40' /></div><br/>Select Rows in Postgres"]
n5["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/postgres.svg' width='40' height='40' /></div><br/>Insert Rows"]
n6["<div style='background:#f5f5f5;padding:10px;border-radius:8px;display:inline-block;border:1px solid #e0e0e0'><img src='https://flowpast.com/wp-content/uploads/n8n-workflow-icons/postgres.svg' width='40' height='40' /></div><br/>Update Rows"]
n1 --> n5
n1 --> n6
n0 --> n3
n0 --> n4
n3 --> n2
n4 --> n1
n2 --> n1
end
%% Styling
classDef trigger fill:#e8f5e9,stroke:#388e3c,stroke-width:2px
classDef ai fill:#e3f2fd,stroke:#1976d2,stroke-width:2px
classDef aiModel fill:#e8eaf6,stroke:#3f51b5,stroke-width:2px
classDef decision fill:#fff8e1,stroke:#f9a825,stroke-width:2px
classDef database fill:#fce4ec,stroke:#c2185b,stroke-width:2px
classDef api fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef code fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
classDef disabled stroke-dasharray: 5 5,opacity: 0.5
class n0 trigger
class n3,n4,n5,n6 database
classDef customIcon fill:none,stroke:none
class n1,n4,n5,n6 customIcon
The Problem: Your Sheet and Database Drift Apart
Most teams start with a Sheet because it’s quick. Then the business grows, Postgres gets introduced for reporting, product data, or integrations, and suddenly you have two copies of the same truth. The messy part is the gap between them. CSV exports get forgotten, imports fail because a date column changed format, and duplicates creep in because nobody’s sure what the “unique key” is anymore. After a few weeks, you’re spending time debating numbers instead of using them.
It adds up fast. Here’s where it breaks down.
- Manual exports turn into a recurring task that steals about an hour every week.
- Small formatting changes in Sheets can cause database inserts to fail, which you often notice days later.
- Updates don’t propagate, so Postgres looks “correct” while being stale.
- Teams create one-off scripts that nobody wants to own, so the sync quietly stops.
The Solution: Scheduled Google Sheets → Postgres Sync
This workflow runs on a timed schedule and does one job well: it keeps a Postgres table in line with what’s currently in Google Sheets. First, it pulls the latest records from your sheet and fetches the current rows from Postgres. Then it extracts the key fields you care about (the ones that define identity and “what changed”). From there, it compares both datasets to find two buckets: rows that exist in Sheets but not in Postgres (new records), and rows that exist in both but don’t match anymore (updated records). Finally, it inserts what’s missing and modifies what changed, so Postgres mirrors the sheet without constant babysitting.
The workflow starts with a schedule trigger. Google Sheets and Postgres are queried in parallel, the results are compared, and the workflow routes changes into either “insert” or “update” actions. When it finishes, your database reflects the sheet’s current state.
What You Get: Automation vs. Results
| What This Workflow Automates | Results You’ll Get |
|---|---|
|
|
Example: What This Looks Like
Say your team updates a lead tracker in Google Sheets and you use Postgres to power reports. Without automation, a weekly export might take 20 minutes, plus another 40 minutes to fix bad dates, duplicates, and failed imports. Call it about an hour, every week, and that’s when everything goes smoothly. With this workflow, you set a schedule once, let it fetch both datasets, and Postgres updates automatically. Your “manual time” drops to a quick spot-check now and then.
What You’ll Need
- n8n instance (try n8n Cloud free)
- Self-hosting option if you prefer (Hostinger works well)
- Google Sheets for the editable source dataset.
- Postgres to store and serve consistent data.
- Google credentials (connect via n8n’s Google Sheets credential).
Skill level: Beginner. You’ll mostly map fields and confirm your unique key for matching rows.
Don’t want to set this up yourself? Talk to an automation expert (free 15-minute consultation).
How It Works
A timed schedule kicks things off. n8n runs this workflow automatically, so your sync doesn’t depend on someone remembering it on Fridays.
Both systems are pulled in parallel. Google Sheets provides the current spreadsheet records, and Postgres returns the current rows from the target table.
Key fields are extracted and compared. The workflow isolates the identifiers and relevant columns, then compares the two datasets to detect what’s new and what changed.
Postgres gets updated. New records are inserted, and existing ones are modified so the database mirrors the sheet as closely as you need.
You can easily modify one-way Sheets → Postgres to run Postgres → Sheets instead, or make it a two-way sync with some guardrails. See the full implementation guide below for customization options.
Step-by-Step Implementation Guide
Step 1: Configure the Schedule Trigger
Set the workflow to run on a fixed schedule so it can regularly sync Google Sheets data into your database.
- Add and open Timed Schedule Start.
- In Rule, set the interval to
hours(as shown in the workflow). - Confirm Timed Schedule Start is connected to both Fetch Sheet Records and Query Postgres Rows.
- Note that Timed Schedule Start outputs to both Fetch Sheet Records and Query Postgres Rows in parallel.
Step 2: Connect Google Sheets
Pull the source data from your spreadsheet.
- Open Fetch Sheet Records.
- Set Document to
[YOUR_ID]and Sheet toSheet1(gid=0). - Credential Required: Connect your Google Sheets credentials.
- Connect Fetch Sheet Records to Extract Key Fields.
[YOUR_ID] is left unchanged, the workflow will fail to find your spreadsheet.Step 3: Set Up Data Preparation and Comparison
Normalize the sheet data and compare it to existing database rows to determine inserts and updates.
- Open Extract Key Fields and set Field to Split Out to
first_name, last_name, town, age. - Open Dataset Comparison and set Resolve to
preferInput1. - In Merge By Fields, ensure field1 is
first_nameand field2 isfirst_name. - Confirm Extract Key Fields connects to Dataset Comparison input 0 and Query Postgres Rows connects to input 1.
first_name only can cause conflicts if multiple people share the same first name. Consider adding last_name to the merge keys if needed.Step 4: Configure Database Read/Write Operations
Query existing records, then insert new rows and update existing rows in your Postgres table.
- Open Query Postgres Rows and set Operation to
selectand Return All totrue. - Set Schema to
publicand Table totestingin Query Postgres Rows. - Credential Required: Connect your Postgres credentials in Query Postgres Rows.
- Open Insert Database Rows and set Schema to
publicand Table totesting. - In Insert Database Rows, keep Columns mapping as auto-map input data with
first_name,last_name,town, andage. - Credential Required: Connect your Postgres credentials in Insert Database Rows.
- Open Modify Database Rows, set Operation to
update, and set column values to={{ $json.first_name }},={{ $json.last_name }},={{ $json.town }},={{ $json.age }}. - In Modify Database Rows, set Matching Columns to
first_nameandlast_name. - Credential Required: Connect your Postgres credentials in Modify Database Rows.
- Confirm Dataset Comparison outputs to Insert Database Rows and Modify Database Rows in parallel.
Step 5: Test and Activate Your Workflow
Run a manual test to verify the full sync, then enable the workflow for scheduled operation.
- Click Execute Workflow to run a manual test.
- Verify that Fetch Sheet Records returns rows and Query Postgres Rows pulls existing database entries.
- Confirm Insert Database Rows adds new records and Modify Database Rows updates matches based on
first_nameandlast_name. - When results look correct, toggle the workflow to Active to enable scheduled runs.
Common Gotchas
- Google Sheets credentials can expire or need specific permissions. If things break, check the connected Google account and sharing access to the spreadsheet first.
- If you’re using Wait nodes or external rendering, processing times vary. Bump up the wait duration if downstream nodes fail on empty responses.
- Default prompts in AI nodes are generic. Add your brand voice early or you’ll be editing outputs forever.
Frequently Asked Questions
About 30 minutes if your sheet and table are already defined.
No. You’ll connect accounts and map the fields you want to keep in sync.
Yes. n8n has a free self-hosted option and a free trial on n8n Cloud. Cloud plans start at $20/month for higher volume. You’ll also need to factor in Google Sheets and Postgres hosting costs (often already covered).
Two options: n8n Cloud (managed, easiest setup) or self-hosting on a VPS. For self-hosting, Hostinger VPS is affordable and handles n8n well. Self-hosting gives you unlimited executions but requires basic server management.
Yes, but be careful. This template is one-way (Google Sheets into Postgres), so to make it two-way you typically add a second comparison path in the other direction and decide which side wins on conflicts. Many teams also add a “last_updated” field and treat the newest edit as the source. If you don’t define conflict rules up front, you can end up overwriting good data with old values.
Usually it’s permissions. Make sure the connected Google account can access the sheet, then re-authenticate the Google Sheets credential in n8n if it was revoked. If the spreadsheet was moved to a shared drive, that can also change access behavior. Finally, confirm you’re reading the correct tab and range, because an empty range can look like a “failed” sync downstream.
For most small business sheets (a few thousand rows), it runs comfortably on n8n Cloud. If you self-host, the practical limit depends on your server and how heavy your compare step is. If your sheet is huge, consider syncing only changed rows (for example, by filtering on an updated timestamp) instead of pulling everything every time.
Often, yes. Dataset comparison and “insert vs. update” logic is where Zapier-style two-step automations start to feel clunky, and it can get expensive as volume grows. n8n also gives you the option to self-host, which is a big deal if you want unlimited runs and more control over data. That said, if you only need a simple “new row in Sheets → create row in database” flow, Zapier or Make can be quicker to set up. If you’re unsure, Talk to an automation expert and get a straight recommendation.
Once this is running, your Sheet stays easy for humans, and Postgres stays trustworthy for systems. Honestly, that’s the balance most teams are trying to get back to.
Need Help Setting This Up?
Our automation experts can build and customize this workflow for your specific needs. Free 15-minute consultation—no commitment required.
