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We are considering using AWS Timestream to store financial transactions from various sources for users. Any solution needs to be able to support ~4k transactions per user per year for 1 million users. Some of the important requirements are:

  • Be able to update transaction amount for three months in the past
  • Calculate daily, weekly and monthly balances by tallying up amounts in real time
  • Balances need to reflect edited transaction amounts, so we'd need to recalculate these in real time often.

Is a time series database a good fit for something like this in terms of real time AND historical record availability?

A few things that worry me about timestream:

  • Can't delete records at all. If bad data enters your system, its going to be extremely difficult to clean it.
  • No backups offered by AWS, we'd have to write something custom for this.

Are there perhaps better time series databases I should consider?

Thanks!

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    That doesn't look like a time series database use case at all. A typical banking application, suitable served by any relational database. A time series database might come into play if you have ~4k transactions per second for 1 million users.
    – mustaccio
    Sep 2, 2022 at 18:38
  • I was going to say, I don't see why the standard relational database management system couldn't handle your use cases either. There's nothing outside the norm here.
    – J.D.
    Sep 2, 2022 at 18:54

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If by "financial transaction" you mean stock ticker or bids to an exchange then yes, timeseries DB is built for this sort of thing.

If instead you mean something like double entry book keeping then a relational database (with transactions) is better suited.

Four billion transactions per year works out at about 600 transactions per second on average over typical office hours. This is busy but not cutting-edge by current standards.

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  • And remember that you don't have to put all the users in a single database. This is especially so in the cloud, where having additional databases doesn't increase your operational cost and complexity.
    – David Browne - Microsoft
    Sep 4, 2022 at 22:36

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