Integrated Multi-Source Database and API Data Consolidation - n8n Workflow

Data Analysts and BI Specialists needing automated, cross-platform reporting.
Businesses using multiple databases (PostgreSQL, MongoDB, MS SQL) who require unified views.
Users looking for advanced n8n templates for complex data pipeline construction.
Automation experts seeking to deploy a reliable, scheduled n8n trigger for data synchronization.

Managing data spread across different systems—relational databases, document stores, flat files, and analytical platforms—is a major challenge. This highly efficient n8n workflow solves this by creating a robust ETL (Extract, Transform, Load) pipeline. This particular n8n workflow is designed to run on a set schedule, extracting data simultaneously from five distinct sources: Google Sheets, PostgreSQL, MongoDB, Microsoft SQL Server, and Google Analytics. By leveraging the parallel processing capabilities of n8n, this automation dramatically reduces the time required for manual data consolidation. The resulting output is a standardized master report in Google Sheets, ensuring consistency and accuracy across all your business metrics. This n8n workflow acts as a centralized reporting solution, providing actionable insights from disparate data silos.

The entire process begins with a powerful scheduling n8n trigger.

1. Scheduled n8n Trigger: The Schedule Trigger n8n node initiates the workflow on Monday, Wednesday, and Friday.


2. Parallel Data Extraction: The n8n workflow simultaneously calls five different source systems: fetching customer data from PostgreSQL, document records from MongoDB, transactional details via MS SQL query, user activity from Google Analytics, and lead information from an input Google Sheet.


3. Source Tagging (Pre-Processing): After extraction, each data stream passes through a dedicated Function n8n node (e.g., 'Add MongoDB Source ID'). This crucial step attaches a unique source identifier to every item, ensuring traceability and preventing confusion when datasets are combined.


4. Consolidation: The central Merge n8n node accepts all five parallel inputs and combines them into a single, comprehensive dataset.


5. Schema Standardization: The combined data enters the Process Merged Data Function n8n node. This step is where data cleaning, alignment, and schema standardization occur, mapping heterogeneous fields (like names, emails, and statuses) into the required output format (Name, Email, Title, Company, etc.).


6. Final Reporting: The standardized data is finally written to the designated output Google Sheet using the Final Google Sheet n8n node. This node handles appending or updating records based on the flow’s logic, completing the automated reporting cycle. This powerful n8n workflow provides a complete data consolidation solution.

To deploy this automated n8n workflow, follow these steps:

1. Import the n8n Workflow: Copy the provided JSON and import it directly into your n8n instance using the 'New' -> 'Import from JSON' option.


2. Credential Setup: You must configure credentials for all resource n8n nodes:

1. Configure Output: In the Final Google Sheet n8n node, replace YOUROUTPUTGOOGLESHEETSID and ensure the column schema matches the output generated by the Process Merged Data n8n node.


2. Activate: Save the n8n workflow and set the toggle to 'Active' to start the scheduled automation.

This complex n8n workflow utilizes numerous specialized nodes:

Schedule Trigger (n8n trigger): The starting n8n trigger for the workflow, set to run three times a week.
Google Sheets Source (n8n node): Reads lead or customer data from a specified input spreadsheet.
PostgreSQL Source (n8n node): Executes a SELECT query to retrieve customer records from the PostgreSQL database.
MongoDB Source (n8n node): Queries a specific collection (yourcollectionname) to retrieve up to 1000 NoSQL documents.
Microsoft SQL Server (n8n node): Runs an arbitrary SQL query against the MS SQL Server for transactional data.
Google Analytics (n8n node): Fetches high-level user activity data based on a specified view.
Function Nodes (e.g., 'Add Sheets Source ID'): Essential pre-processing n8n node used to tag incoming data with a source identifier before merging, maintaining data lineage.
Merge (n8n node): A critical corelogicflow_control node configured with five inputs, responsible for combining all data streams into a single dataset for subsequent processing.
Process Merged Data (Function n8n node): Contains custom Javascript logic to clean, align, and standardize the diverse data schemas into a unified report format.
Final Google Sheet (n8n node): The final action, using the 'appendOrUpdate' operation to write the consolidated and standardized data back into the output Google Sheet.