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Introduction The setup Laying the foundation The foundation: schemas and user roles for modularity Domains Accounts, managed and external Transfers, constrained by a state machine and temporal periods Transfer state history Account auditing Transactions, the immutable events On maintaining business rules via meaningful constraints The transfer state machine Transactions must fall within the transfer period Pending transactions require a pending transfer No future transactions when closing a transfer On capacity planning Working set estimation On write throughput Enabling HOT Updates for Transfers Making sure there are no Unused indexes OLTP Listing The history of a transfer OLAP Balance ledger Incremental maintenance via triggers On serializable isolation On decoupling Benchmarking the startup scenario Seed data Write script: full transfer lifecycle Read script: activity stream and balance Running the benchmark Results Conclusion Appendix A: Full code suite. Introduction There is a deep cultural reflex in modern engineering: whenever a problem appears, reach for a packaged solution instead of thinking from first principles. The result is architectural cargo culting and lots of missed opportunities. Some intentionally absurd-but-familiar examples:


The row-level locking and
SKIP LOCKEDseem like appropriate features for a SQL-based DBMS. I find it odd that it’s not more common, actually. Even MSSQL doesn’t make any promises about locking just a row and might decide to lock a whole page instead, from what I read anyway.NOTIFY/LISTEN might be scope creep though. I’m not really sure what led to it being implemented.