![]() ![]() This gets a little more complex when you have an example as in example 2. Even if transaction_datetime was part of the key, the problem is that consider the actual data values – one transaction may have occurred at “ 10:23:24.234” and the next transaction may have occurred at “ 10:26:12.567” – the issue is that with normal relational models, the primary/foreign key relationship keys have to have the same values….which it obviously doesn’t in this case. For example, consider the following two sample SQL tables: /* example 1 */Ĭonsider example 1. The primary key likely is a combination of account_id + transaction_id. Using normal primary key/foreign key relationships, it is then difficult to create a relationship that would “tie” the transactions into a sequence. I think the reason we get this question a lot is that while RDBMS systems may have internal triggers to maintain the data – the underlying relational model implementation doesn’t describe it well – or is limited at best. No property – just a relationship that infers a sequence – for example parent -> childĪnd we wish to look at the data from a sequential view point.A pair of dates/datetimes that represent the start effective and end effective dates.A single date or datetime property that represents when the event happened or will happen. ![]() When we talk about time series or longitudinal data, we are referring to any data entities that have: One of the most common modeling questions we get asked is how to model time series/sequential/longitudinal data in Neo4j. ![]()
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