How to Import Excel Data to PostgreSQL: 5 Easy Methods (2026)

“People couldn’t make sense of numbers before, and now everybody can.” Satya Nadella said that about Excel. He was right. Excel made data accessible to everyone, not just analysts or engineers.

The problem is that accessible is not the same as scalable. Excel breaks under concurrent access. It struggles with large datasets. It was never built for the kind of relational querying that production applications need. PostgreSQL was.

For teams that have outgrown their spreadsheets, the next step is moving that data somewhere it can actually be queried, joined, and relied on. That means getting it into PostgreSQL.

There are five ways to do that. Some take minutes. Some require technical setup. The right one depends on how often you need to move data, how technical your team is, and whether you need a one-time import or an automated recurring data pipeline. This guide covers all five, with enough detail to execute whichever method fits your situation.

Prerequisites for Importing Excel Data to PostgreSQL

Before you begin, make sure the following are in place across all five methods.

1. A running PostgreSQL instance

You need access to a PostgreSQL database server. The current stable release is PostgreSQL 18.4, released May 14, 2026. Supported versions include 14, 15, 16, 17, and 18. If you are running PostgreSQL 13 or earlier, note that these versions are now end-of-life and no longer receive security patches. You will need the following details to connect:

• Host or IP address of the PostgreSQL server
• Port number (default is 5432)
• Database name
• Username and password with write access to the target database

2. Your Excel file in the right format

Most methods in this guide require your Excel data to be structured with column headers in the first row and no merged cells, blank rows, or formatting-only rows. The accepted file formats are:

• .xlsx (Excel 2007 and later, recommended)
• .xls (older Excel format, supported by most tools)
• .csv (comma-separated, required for Methods 3 and 4)

If your file has multiple sheets, identify which sheet contains the data you want to import before you begin. Most tools require you to specify the sheet name during setup.

3. A target table in PostgreSQL (for manual methods)

Methods 3, 4, and 5 require a table to already exist in your PostgreSQL database before you import data. The table columns must match the column names and data types in your Excel file. If the table does not exist, you will need to create it first using a CREATE TABLE statement or pgAdmin’s table creation interface.

4. Admin or write access to your PostgreSQL database

You need sufficient permissions to connect to the database and write data to the target table. If you are working in a shared or production environment, confirm with your database administrator that your user account has INSERT and COPY privileges on the target table.

Good data management practices recommend keeping a record of which users have write access to production tables.

Method 1: Using Hevo

Hevo Data is a fully managed, no-code ELT platform that makes moving Excel data to PostgreSQL simple, reliable, and transparent. It connects to Excel files stored in Google Drive, OneDrive, Dropbox, Box, and Amazon S3, and loads them into PostgreSQL automatically with schema mapping, error handling, and full data integration visibility built in. 

This is the only method on this list that works for both one-time imports and recurring automated pipelines without any manual intervention after setup.

Step 1. Create a New Pipeline

• Log in to Hevo.
• Click “+ Create Pipeline”.
• Choose File Storage as the source.

Step 2. Choose Your Excel File Source

Select File Storage as the source type. Hevo supports the following file storage sources for Excel files:

• Amazon S3
• Google Drive
• Dropbox
• Box
• OneDrive

Select your source → Authenticate → Select your Excel file(s).

Step 3. Configure File Format

Set the file type to Excel. Specify the sheet name and confirm whether the first row contains column headers. Choose your sync frequency: one-time import or a recurring schedule. Hevo auto-detects data types from your file. You can review and adjust them manually before the pipeline runs.

Step 4. Set PostgreSQL as Destination

Click Add Destination and select PostgreSQL. Enter your connection details:

• Database host
• Port (default 5432)
• Database name
• Username and password

Click Test Connection, then Save and Continue. Hevo automatically creates the target table in PostgreSQL if it does not already exist.

Step 5. Mapping & Transformation (Optional)

Review the column mapping between your Excel file and the PostgreSQL destination.Apply data transformation logic if needed using Hevo’s drag-and-drop Visual Flow or Python-based scripting for more complex cases. This step is optional. Hevo handles standard mapping automatically.

Step 6. Activate the Pipeline

Click Activate to start the pipeline. Monitor the run from your Hevo dashboard. You will see row-level logs, sync status, data lineage, and any anomalies flagged in real time.

“We had numerous files that needed rapid ingestion and a pipeline established without being hindered by server infrastructure or schema complexities. Hevo enabled us to achieve this efficiently.”

 ~ Mike C., SVP of Technology (G2 Review)

See how Hevo moves Excel data to PostgreSQL automatically, without a single manual step.See Hevo in Action

Method 2: Using ODBC Drivers to Import Excel to PostgreSQL

Get & Transform (Power Query) can be used to set up an Excel PostgreSQL connection using ODBC. This approach presupposes you’ve installed a PostgreSQL ODBC Driver.

Step 1: Install ODBC Drivers for PostgreSQL

• The first step in Excel to PostgreSQL data transfer is to install the “ODBC Driver.” The PostgreSQL ODBC 64-bit driver is available for download. On the machine where the Secure Agent is installed, install the PostgreSQL ODBC driver.

Step 2: Configure the Postgres ODBC Driver in Excel

• Expand the “Get Data” drop-down box after clicking “Data” in Excel. Select “From Other Sources > From ODBC” from the drop-down menu.

Step 3: Authorize Connection With PostgreSQL

• Choose your data source name in the “From ODBC dialogue (DSN).” You can expand the “Advanced Options” dialogue box and input the connection string for your data source if you haven’t yet established your ODBC Driver (without credentials, which are defined in the credentials dialogue box in the next step).
• You can also enter a SQL query that will be performed immediately after connecting to the data source. Click the “OK” button.

• Select the database and input your credentials in the dialog box, then click “Connect” if you’re using a database “Username” or “Password”. Select “Default” or “Custom” and connect if your database is not password-protected or if you’ve previously entered your credentials in the ODBC Data Source settings.

Step 4: Load Data in Microsoft Excel

• Select the table from which you wish to retrieve data in the pop-up box and click “Load.”

• The table’s data will be displayed in an Excel spreadsheet, where you can interact with it further.

• You have successfully completed the data transfer via ODBC Driver.

Learn more about – How to import Excel into MySQL and import Excel into Bigquery.

Method 3: Integrating Excel and PostgreSQL via CSV Files Using DBeaver

DBeaver is a free, open-source database tool that can transfer data from a CSV file directly into PostgreSQL using its Data Transfer wizard. This method requires DBeaver to be installed and connected to your PostgreSQL instance.

Step 1: Save Your Excel File as CSV

Open your Excel file. Click File, then Save As. In the format dropdown, select CSV UTF-8 (Comma delimited) (*.csv) and click Save. Note the folder where you saved the file as you will need it in the next step.

Step 2: Connect to CSV as a Data Source in DBeaver

Open DBeaver. Click the New Database Connection button or go to Database > New Database Connection. In the Connect to a database dialog, scroll through the list or type CSV in the filter box. Select CSV and click Next. Browse to the folder where your CSV file is saved and complete the connection setup. Each CSV file in the folder will appear as a table in DBeaver’s Database Navigator.

Step 3: Export Data from the CSV Source to PostgreSQL

In the Database Navigator panel, expand your CSV connection and locate the table corresponding to your Excel file. Right-click the table and select Export Data from the context menu.

In the Data Transfer wizard that opens, set the target as your PostgreSQL connection. On the Tables mapping screen, confirm that the source table maps to the correct target table in PostgreSQL. The Mapping column will show “create” if the table does not yet exist in PostgreSQL, or “existing” if it does. Click Next to proceed through the Extraction settings and Data load settings screens, then click Proceed to start the transfer.

Step 4: Verify the Data in PostgreSQL

Once the transfer completes, open a new SQL editor in DBeaver connected to your PostgreSQL instance and run:

sql

SELECT * FROM your_table_name;

Your Excel data is now loaded into PostgreSQL.

Method 4: Transfer data from Excel to a PostgreSQL Database Using pgAdmin

Step 1: Save as CSV

• Convert your Excel spreadsheet into a CSV file. To do this, click on “File,” then save as. In the drop-down bar that appears, pick “CSV (Comma delimited),” and then hit “Save.”

Step 2: Create an empty table in pgAdmin

• Create an empty table in PostgreSQL with identical column names, data types, and column constraints as your Excel sheet’s columns.

Step 3: Use “Import/Export”

• In PostgreSQL, right-click on the newly formed table; a selection of choices will display; select the “import/export” option.

• At this stage, a dropdown menu displays. Here’s how to use the dropdown box:
  • Choose the “Import” option.
  • On the file name tab, pick your excel sheet from your PC by clicking the select file “(…)” button.
  • Choose “yes” for the header choice.
  • Choose the “comma (,) delimiter” as the delimiter choice.
  • Click “OK.”

Step 4: Point to your CSV

• If all rules are followed correctly, an import task is produced. A process observer appears to assist you in keeping track of what’s going on.

• You’ve successfully loaded the table into your relational database management system.

Method 5: Move Data From PostgreSQL to Excel Using Microsoft Query

Microsoft Query is a legacy Excel feature that allows you to pull data from external sources including PostgreSQL directly into an Excel sheet. This is useful for reporting and analysis workflows where you need live or periodically refreshed PostgreSQL data inside Excel.

Note: Microsoft moved this feature to the Legacy Wizards section in Microsoft 365. The navigation path has changed from previous versions.

Step 1: Open Microsoft Query from Excel

Open the Excel sheet where you want to import PostgreSQL data. Click the Data tab in the ribbon. Click Get Data, then hover over Legacy Wizards, and select From Microsoft Query (Legacy) from the submenu.

Step 2: Select Your PostgreSQL Data Source

In the Choose Data Source dialog, select your PostgreSQL DSN from the list. Make sure the option “Use the Query Wizard to create/edit queries” is checked. Click OK.

Step 3: Enter Your Database Connection Details

Enter your PostgreSQL database name, username, and password when prompted. Click OK to establish the connection.

Step 4: Select Tables and Import Data

In the Query Wizard, select the tables you want to import into Excel. Use the arrow button to add columns to your query. You can optionally apply filters or sort data before importing. Click Finish to load the data into your Excel sheet.

Once complete, your PostgreSQL data will appear in the Excel sheet. You can refresh it at any time by going to Data > Refresh All to pull the latest data from your PostgreSQL database.

You can also use additional features under the Get Data tab, including Power Pivot for importing and filtering data from PostgreSQL with advanced data modeling capabilities, and the Query Wizard for building and modifying queries to retrieve specific records from your database.

Comparing the 5 Methods: Which Excel to PostgreSQL Approach Is Right for You?

Here is a side-by-side comparison of all five methods to help you pick the right one for your situation.

If you are new to how data moves between systems, this guide to ETL data modeling provides useful context before you begin.

Method	Technical Level	Best For	One-Time or Recurring	Setup Time	Cost
Hevo Data	None	Teams needing automated, recurring pipelines from Excel to PostgreSQL without writing code	Both	Minutes	Free tier available; paid plans from $399/month
ODBC Driver	Intermediate	Analysts who need a live, refreshable connection between Excel and PostgreSQL	Recurring	30 to 60 minutes	Free (driver)
CSV via DBeaver	Beginner to Intermediate	Developers or analysts comfortable with a GUI database tool for one-off imports	One-time	15 to 30 minutes	Free
pgAdmin	Beginner	DBAs and developers already using pgAdmin who need a quick one-off import	One-time	10 to 20 minutes	Free
Microsoft Query	Intermediate	Excel users who need to pull PostgreSQL data into Excel for reporting without leaving Excel	Recurring	30 to 60 minutes	Free (requires ODBC driver)

How to choose:

• Need it done once and fast with no setup: use pgAdmin or DBeaver. Both are free open-source ETL tools that work without any licensing cost.
• Need a live, refreshable connection inside Excel: use ODBC or Microsoft Query
• Need recurring automated imports without manual steps: use Hevo

Not sure which method fits your team? See how Hevo handles Excel to PostgreSQL without any technical setup.Schedule a Demo

Conclusion

This article teaches you about Excel to PostgreSQL. It provides in-depth knowledge about the concepts behind every step to help you understand and implement them efficiently. PostgreSQL is a great tool for storing your business data. However, at times, you need to transfer this data from multiple sources to your PostgreSQL account for further analysis.

If you want to transfer data into your desired database/destination like PostgreSQL, then Hevo Data is the right choice!

Hevo Data is a no-code data pipeline solution that can help you import data from a vast sea of sources like Google Sheets to your desired destination such as PostgreSQL, data warehouses, or BI tools.

Try Hevo and see the magic for yourself. Sign up for a free 14-day trial to streamline your data integration process. You may examine Hevo’s pricing plans and decide on the best plan for your business needs.

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