How to Connect Postgres to Google Sheets: 3 Easy Methods

‍‍Pull raw data, build auto-updated reports dashboards, and find the real-time information you need. Follow this step-by-step explanation to learn how to automatically retrieve data from your Postgres and import it into Google Sheets with a script you can copy and paste into Google Apps Script.

Here are some of the best ways to connect Postgres to Google Sheets, from third-party tools to on-script creation. This guide is helpful for anyone, from a data enthusiast wanting to streamline the workflow to a professional who wants a team in tune with the most recent information.

What are Google Sheets?

Google Sheets is a cloud-based spreadsheet application developed by Google that allows you to access, edit, and collaborate from anywhere on the Internet. It integrates seamlessly with other apps, such as Google Drive and Google Docs, enabling a smooth document-linking process.

What is PostgreSQL?

PostgreSQL, often called “Postgres,” is a powerful, open-source object-relational database known for its reliability, robustness, and extensive SQL support. PostgreSQL supports various SQL features, including complex queries, joins, subqueries, triggers, views, and window functions.

Importance of Integrating Postgres to Google Sheets

• Real-time Data Reporting: You can generate real-time reports and dashboards directly by connecting Postgres to Google Sheets. This helps you respond quickly to changing customer demands.
• Automated Data Import: Integration can automate importing your data from Postgres to Google Sheets. This reduces human intervention, which ultimately minimizes errors.
• Streamlined Workflow: Integrating Postgres with Google Sheets streamlines workflows because sharing and updating data is easy.

Methods to migrate data from Postgres to Google Sheets

Let’s discuss a few methods by which we can integrate Postgres to Google Sheets.

Method 1: Using Third-Party Tools

1.1 Coefficient

It is a tool to import live data into spreadsheets automatically. Some of its features include :

• Quick Integration: Import your data in seconds.
• Live Analytics: Unlock Live Data and Dashboards for your team.
• Auto Update: Updates systems directly from your spreadsheets.

Steps to install and use Coefficient for data migration

• Select Extensions → Add Ons → Get Add Ons.

• Search for Coefficient in Google Workspace Marketplace and install it.

• After installation, Select Extensions → Coefficient → Launch.

• Fill out your details. Select Import from the Coefficient Panel on your screen’s right side.

• Click PostgreSQL from the list of Data Sources provided and enter your host and database name. Also, if you scroll down, fill out the username and password fields.

Note: The Port field will be filled out by default to 5432; do not change it.

• Select the Data you want to import and Click on Export. The data will be auto-populated from Postgres to Google Sheets, as shown in the screenshot below.

Limitations

• Limited Support to Databases: It does not support specific versions of databases.
• Performance Consideration: Depending upon the volume of your data to be migrated, its performance may vary.

    1.2 Actiondesk

     It is a tool for centralizing all your data sources in one place. 

• Single Source: All of your data is centralized in a data warehouse.
• Auto Transformation: It is automatically transformed.
• Live Analytics: You can also visualize or analyze your data.

Note: Datadog has now acquired this product.

1.3 Estuary Flow

Flow helps you define data pipelines, known as Data Flows, that connect multiple data systems, APIs, and storage and optionally transform your data. It has three main components:

• Capture: Flow ingests your data from an outside source.
• Collections: Flow maintains the captured data in the cloud storage you provided.
• Materialization: Flow pushes your data to your target destination.

Steps to use Estuary Flow to migrate data :

• Log in to Estuary Flow, and you will be directed to their dashboard. Search for Connectors and select PostgreSQL → Capture.

• Enter your hostname, port number, username, password, and database name. Click on Next.

Note: Testing, saving, and capturing your data will take some time. You will receive a Success message on the screen when you complete them.

• Select a connector for Destination, Google Sheets → Capture. Enter the link to the spreadsheet you want to import into.

• Select Save and Publish. Once successful, your data will automatically be migrated from Postgres to Google Sheets.

Limitations :

• Complex Transformations: To perform complex data transformations, you require more customization or scripting than is possible with Estuary Flow.
• Dependency on Third-party Services: Certain aspects of Estuary Flow might depend on external APIs or services. You should know these dependencies and their possible effects on migration operations.

1.4 Hevo Data

Alternatively, you can use Hevo Data for an automated data integration process. You can sync your Source and Destination in minutes, and we will do the rest.

Integrate your Postgres database with Hevo. Schedule a demo with us entirely free of cost.

Method 2: Google Apps Script

Google Apps Script is a scripting platform developed by Google for lightweight application development on the Google Workspace platform.

• Seamlessly integration: Apps Script with Google Workspace apps allows you to automate processes in Google Sheets, Docs, Slides, Forms, and Gmail.
• Built-in script editor: It offers an online integrated development environment (IDE), allowing you to write, modify, debug, and manage your scripts within your browser.

      Steps to migrate data using Google App Script :

• Create a new Google Sheet and copy its URL. Go to Extensions → Apps Script.

An Apps Script editor will open in a new tab.

• You can retrieve your data from PostgreSQL to Google sheet with a sample script below:

var dbUrl = 'jdbc:postgresql://<HOST>:<PORT>/<DATABASE>';
var user = '<USERNAME>';
var userPwd = '<PASSWORD>';

function importDataFromPostgres() {
  // Connect to the PostgreSQL database
  var conn = Jdbc.getConnection(dbUrl, user, userPwd);

  // Perform a query
  var stmt = conn.createStatement();
  var results = stmt.executeQuery('SELECT * FROM your_table LIMIT 10');  // Modify your query as needed

  // Get the active spreadsheet
  var sheet = SpreadsheetApp.getActiveSpreadsheet().getActiveSheet();

  // Clear any existing content
  sheet.clear();

  // Get the number of columns in the result set
  var numCols = results.getMetaData().getColumnCount();

  // Write column headers
  var headers = [];
  for (var col = 1; col <= numCols; col++) {
    headers.push(results.getMetaData().getColumnName(col));
  }
  sheet.appendRow(headers);

  // Write data rows
  while (results.next()) {
    var row = [];
    for (var col = 1; col <= numCols; col++) {
      row.push(results.getString(col));
    }
    sheet.appendRow(row);
  }

  // Clean up
  results.close();
  stmt.close();
  conn.close();
}

Note: Replace the placeholder values in dbUrl, user, and userPwd with your actual PostgreSQL database host, port, database name, username, and password.

• To configure the JDBC Driver in your Google Apps Script. Go to Libraries, type the Script ID, and Click on Add, as shown in the below image:

• Run the Migration Script. This script will connect to your database to fetch and insert data from Postgres to Google Sheets.

Limitations :

• Limited Programming Language Support: It mainly supports Javascript, which might need some of the features other languages provide.
• Integration Limitations: While it offers integrations with Google Workspace Apps, integrating external services or non-Google APIs may require more complex setups.

Method 3: Connect Postgres to Google Sheets using Zapier

 Zapier lets you connect PostgreSQL with thousands of popular apps, automating your work and freeing up time for what matters most—no code required.

• Using a straightforward visual builder, users may develop automated workflows or “Zaps.” Zaps consist of actions (tasks carried out automatically) and triggers (events that initiate the automation).
• Zapier supports multi-step Zaps where multiple actions can be carried out together, allowing for complex automation sequences.

      Steps to migrate data using Zapier :

• Log in to Zapier. Click on +Create → Zaps.

• You will be directed to a Zaps Editor Page. Click on Trigger to connect to the PostgreSQL as the source. Click on Action to connect to Google Sheets as the destination.

Note: If you are done with your configurations, Publish your Zap.

Limitations :

• Performance: Performance problems might arise from large-scale data migrations because of action triggers and large-scale dataset processing delays. It may impact the dependability and speed of data transfers.
• Limited Error Handling: Although Zapier offers error logs and alarms for unsuccessful activities, complex error handling and retry procedures could call for further tools or customized configurations.

Detailed Comparison of the Methods

Parameters	Third-Party Tools	Google Apps Script	Zapier
Ease of Setup	Very Easy	Moderate	Easy
Technical Requirements	Minimal; primarily GUI-based	High; Requires Javascript proficiency	Low; mostly GUI-based
Cost Implications	Moderate; mostly tier-based pricing	Free	Low
Maintenance	Minimal; managed by the provider	High; scripts may need updates and monitoring	Low; managed by the provider
Reliability	High	Moderate; depends on script quality	High

Depending on your specific needs, such as budget constraints, technical expertise, and ease of maintenance, you can choose the best method for migrating data from Postgres to Google Sheets.

Best Practices for Data Integration

Let’s dive into some best practices for data integration. These tips will help you ensure data accuracy, handle large datasets efficiently, and keep your data fresh and reliable.

1. Data Accuracy
   • Source Validation: To ensure data quality, validate your data at the source before its integration. This way, verification for errors, inconsistencies, and missing values will be done right at the origin.
   • Consistent Data Format: Ensure consistency for all your data formats and standards. This will help reduce the possibility of errors from the integration stage itself.
   • Implement Data Quality Check: You can periodically run data quality checks to identify and fix issues. This could include checking data ranges, duplicates, or whether all the mandatory table fields are filled.
2. Working with Large Datasets
   • Incremental Loads: Employ incremental loads to load only new or updated records, not the entire datasets. This will put less load on your system and will be faster.
   • Batch Processing: Split enormous data into smaller and, hence, more separately manageable chunks to decrease the probability that failure or individual faults within a batch will affect the whole population.
   • Query Optimization: Always remember to optimize every query you pass through a database for top performance. This can include indexing key columns or fine-tuning your SQL commands to reduce the processing time as much as possible.
3. Schedule Updates Regularly
   • Schedule automated refreshes: Automize your data updating process. Most tools for setting updates offer scheduling.
   • Monitor data pipelines To confirm your pipelines are configured correctly and set up alerts on failures or delays.
   • Frequency Requirement: The frequency required should match your business needs. For instance, updating critical data would be done every hour, and less critical data may be updated each day or week.

Conclusion

Today, we discussed different third-party tools like Coefficient and Hevo Data. With their intuitive UI and automated scheduling, third-party tools could be a good choice if you’re looking for a simple setup requiring little technical expertise. 

You can use the rich customization and control that Google Apps Script offers when developing customized solutions that integrate Postgres to Google Sheets. Several variables, including the required level of automation, particular integration needs, and technological know-how, determine the optimal approach.

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FAQs

1. How do I convert Google Sheets to a database?

To convert Google Sheets data into a database, export the data in a structured format such as CSV or Excel. Then, choose a database where you want to import it, and finally, import the data using database management tools like MySQL Workbench and pgAdmin.

2. Can we use Google Sheets as a database?

Yes, Google Sheets can be used as a database in specific scenarios, particularly for small-scale applications or prototyping where simplicity and ease of use are prioritized over advanced database features.

3. Can SQL pull data from Google Sheets?

Yes, SQL can pull data from Google Sheets using external data connectors or by importing Google Sheets data into a traditional database system.

4. Can Google Sheets query a database?

Google Sheets can query data from external databases using Google Sheets’ built-in functions and add-ons.

5. How do I turn a Google sheet into a data table?

To turn a Google Sheet into a data table, ensure your data is well-organized with headers for each column. Select the range of cells containing your data, then click on the “Format” menu and choose “Table.”