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Delta Load

A delta load refers to extracting only the data that has changed since the last time the extract process has run. The most commonly used steps to perform a delta load are:

  1. Ensure there is a modified_at timestamp or incremental id column such as a primary key on the data source.
  2. On the initial run of the pipeline, do a full load of the dataset.
  3. On following runs of the pipeline, query the target dataset using MAX(column_name).
  4. Query the source dataset and filter records where values are greater than the value from step 3.

Delta Load Advantages

  • More resource efficient
  • Easy to implement and maintain
  • Only requires read permissions to perform

Delta Load Disadvantages

  • Does not capture deleted records
  • Requires extra metadata on the source (commonly a unique id or updated timestamp)
  • Does not capture multiple changes between the polling interval. If a row changes multiple times, you may only capture the latest state.
  • Querying the database for changes may impact the database performance.