Advanced ORM: Filtering, sorting & summing 40M financial transactions

TALK: Advanced ORM kung-fu for on-demand filtering, sorting, and summing 40 million financial transactions by Mathias Wedeken

When the base data is a collection of 40 million postings in a table that grows longer every day, distributed across 472,000 accounts on roughly 5,000 properties; when the use case is filtering, grouping, summing, and sorting these; and when all of this has to happen on-demand for users trying to keep track of what the real-time financial situation of their property is- that's when you realise that using the ORM for mere data access and working the data in Python might not be the ticket. And, when users suddenly want to compare their property to some of the 5,000 others, your Python-first approach will expose the users to a considerable wait which, frankly, can be a bit embarrassing. You don't want to be that guy. Mathias Wedeken talked about how he pushed all this heavy lifting to Postgres using the Django ORM and (almost) no raw SQL.

More information: https://2026.djangocon.eu/speakers/NP83RK/

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