Presented by:


Alexey Solovtsov

Alexey has been working as a software engineer for the last 10 years building data-intensive information systems for companies in US and Australia.

No video of the event yet, sorry!

Temporal Tables are useful in scenarios that require tracking history of data changes. Using temporal tables allows to perform data audit of individual records and also to see how entire data sets are changing over time. This is especially useful in the early stages of the development cycle, as it allows to defer date warehouse modeling and implementation and instead focus on delivering an initial set of reports using views over temporal tables. While many enterprise databases have built-in support for temporal tables, Postgres doesn’t provide out-of-the-box solution, but it has all the building blocks such as range types, excellent JSON support, triggers and user functions, to implement custom temporal tables functionality that would fit your needs.
In this session we’ll discuss how to design dedicated temporal database with Postgres to transparently keep the full history of changes for later analysis, separately from the current data, with the minimal impact on the main OLTP workload.

2019 September 20 15:00 PDT
20 min
Winchester (2)
Silicon Valley 2019
Case Studies