Which feature of Databricks allows querying of historical data?

Time travel in Delta Lake is a powerful feature that enables users to query historical data by accessing previous versions of their datasets. Delta Lake maintains a transaction log that records all changes made to the data, allowing users to easily revert or access any prior state without complex data management processes. This is particularly useful for data versioning, auditing, or simply retrieving data as it appeared at a certain point in time.

For instance, if a user needs to analyze trends or investigate changes over time, they can leverage time travel to access the datasets as they were on a specific date or version. This feature enhances data reliability and provides a mechanism for error recovery, enabling organizations to manage datasets with greater flexibility and confidence.

In contrast, job scheduling is focused on automating and managing workflows, data partitioning optimizes query performance by organizing data, and data governance involves policies and processes to ensure data privacy and compliance. While each of these features plays a critical role in data management, they do not directly provide the ability to query historical data as time travel does.