Amazon Redshift will no longer support the use of Python UDFs after June 30, 2026. We will start enforcing it in phases. For more information on the details of Python end of life and migration options, see the [ blog post ](https://amazonaws-china.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/) that was published on June 30, 2025. 

# Amazon Redshift best practices for loading data
<a name="c_loading-data-best-practices"></a>

Loading very large datasets can take a long time and consume a lot of computing resources. How your data is loaded can also affect query performance. This section presents best practices for loading data efficiently using COPY commands, bulk inserts, and staging tables. 

**Topics**
+ [Learn how to load data with a tutorial](c_best-practices-loading-take-loading-data-tutorial.md)
+ [Use a COPY command to load data](c_best-practices-use-copy.md)
+ [Use a single COPY command to load from multiple files](c_best-practices-single-copy-command.md)
+ [Loading data files](c_best-practices-use-multiple-files.md)
+ [Compressing your data files](c_best-practices-compress-data-files.md)
+ [Verify data files before and after a load](c_best-practices-verifying-data-files.md)
+ [Use a multi-row insert](c_best-practices-multi-row-inserts.md)
+ [Use a bulk insert](c_best-practices-bulk-inserts.md)
+ [Load data in sort key order](c_best-practices-sort-key-order.md)
+ [Load data in sequential blocks](c_best-practices-load-data-in-sequential-blocks.md)
+ [Use time-series tables](c_best-practices-time-series-tables.md)
+ [Schedule around maintenance windows](c_best-practices-avoid-maintenance.md)