logo
search
Power Query Problems

How to Fix Power Query Container Error When Reading Large Oracle Tables

Camila MilosovichCamila Milosovich Sep 27, 2026 869 views

Question details

The user needs to resolve an error (0xC0000409) that causes Power Query to fail when loading a large Oracle database table via an ODBC connection.

How to Fix Power Query Container Error When Reading a Large Oracle Table
Product
Microsoft Excel / Power Query
Device & OS
not provided
Scenario
Connecting to and extracting data from a large Oracle 19c database table using the Power Query ODBC connector.
Observed behavior
The connection works for small tables but fails with container error 0xC0000409 when attempting to read large tables.
Before you start

Ensure you have administrative privileges on your computer to update or reinstall ODBC drivers, and verify whether your Office application is 32-bit or 64-bit.

Solution 1Recommended

Update and Match the Oracle ODBC Driver Architecture

Matching the ODBC driver architecture to your application and updating to the latest version often resolves container crashes.

A common cause for container error 0xC0000409 is a mismatch between the bit-version of your Office application and the installed Oracle ODBC driver, or using an outdated driver with bugs handling large memory allocations.

1
Check Office Architecture

Open Excel, go to File > Account > About Excel to verify if your application is 32-bit or 64-bit.

2
Download Matching Driver

Download the corresponding 32-bit or 64-bit Oracle 19c Client and ODBC driver from the official Oracle website.

3
Reconfigure ODBC Data Source

Open the 'ODBC Data Source Administrator' tool on your PC, remove the old connection, and set up a new DSN using the newly installed driver.

Update and Match the Oracle ODBC Driver Architecture
Driver Patches: Ensure your Oracle 19c client is fully patched, as older versions may contain known bugs when handling large data streams.
Free Microsoft Office alternative

Need a Lightweight Alternative for Your Spreadsheets?

If heavy data processing tools like Power Query are causing persistent container errors or slowing down your computer, try WPS Office. It is a free, lightweight Microsoft Office alternative that offers a familiar interface, seamless migration, and excellent format compatibility for all your standard data analysis needs without the bloated overhead.

  1. 1. Download WPS Office: Visit the official WPS Office website and click the free download button.
  2. 2. Install the Software: Run the installer and follow the simple on-screen instructions to complete the setup.
  3. 3. Open Your Spreadsheets: Launch WPS Spreadsheet and immediately open your existing .xlsx data files without any complex configurations.
Free and lightweight alternative to Microsoft Office, avoiding heavy background processes that cause container errors.Highly compatible with Microsoft Excel (.xlsx, .csv) formats for seamless data sharing.Familiar user interface requires no learning curve, allowing for a seamless migration.Built-in basic data import tools that are fast and easy to configure.
microsoft office alternative - wps office

Frequently Asked Questions

What does error 0xC0000409 mean in Power Query?

Error 0xC0000409 is a system error code indicating a 'Stack Buffer Overrun'. In Power Query, this means the background evaluation container crashed unexpectedly, usually due to memory limits, driver bugs, or an architecture mismatch when processing a large volume of data via ODBC.

Can I use a 32-bit Oracle ODBC driver with 64-bit Excel?

No, you cannot mix architectures. Your ODBC driver bit-version must exactly match your Office application's bit-version. If you are using 64-bit Excel, you must install and configure the 64-bit Oracle ODBC driver.

Why does my connection work on small tables but crash on large ones?

Large tables require significantly more memory allocation and processing time. The ODBC driver might run out of allocated system memory, hit an internal timeout limit, or encounter an unsupported data type that is only present deep within the larger dataset.