r/Database

Apologies for the long read in advance but if anyone can help or point me in the right direction, I'd greatly appreciate it :)

Currently doing a practise task which requires me to write a report for a hypothetical company. I am given a spreadsheet (which includes errors and duplication etc) and I have to normalise it from 1NF to 3NF in clear steps which has to be shown. Then I have to import them into Microsoft Access and create an ERD

There are 36 columns included in the spreadsheet
Columns:
ExportRowID, PONumber, POLineNumber, PODate, RequiredDate, POStatus, Priority, SupplierID, SupplierName, SupplierContact, SupplierPhone, SupplierEmail, SupplierAddress, PaymentTerms, PurchasingEmployeeID, PurchasingEmployeeName, EmployeeDepartment, DeliveryLocation, ProductID, ProductName, ProductCategory, UnitOfMeasure, QuantityOrdered, UnitCost, LineAmount, ReceiptNumber, ReceiptDate, ReceivedByEmployeeID, ReceivedByEmployeeName, QuantityReceived, AcceptanceStatus, DeliveryCondition, InvoiceNumber, InvoiceDate, InvoiceAmount, Notes

My attempt (7 tables):
Supplier (SupplierID)
Employee (EmployeeID)
Product (ProductID)
PurchaseOrder (PONumber)
POLine (PONumber + POLineNumber)
Receipt (ReceiptNumber)
Invoice (InvoiceNumber)

Does this look right? I'd also appreciate help with the Access side (relationships and importing from one flat sheet into multiple tables).

Hi

I am experimenting with sqlite on a Macbok Pro M4 - 10 cores machine. I have a pthreads multithreaded program and i am trying to write lots of data to different databases (separate database connections) and (one database file per thread) and they are DIFFERENT files

I have THREADSAFE mode set to 2 (multithreaded) and i open the files with NOMUTEX flag.

Now i have read that the M4 Macbook Pro has a soldered SSD. And it has similar performance to nvme but it is not nvme

I get around 10000 transactions per second in total across all threads.

I tried synchronous=off and that boosts performance to 300000 transactions per second

Increasing the number of items inserted per transaction scales. But the number of transactions doesnt

I feel that IO is being serialised.

Some parts of web seem to suggest it is serialised. But i thought ssds can run things in parallel.

Does anybody know anything about parallel IO or if i need to enable it on macos?

I havent tried it on Linux or Windows

Would you expect transactions to scale by number of threads?

I have read about iokit but i have no knowledge of how to use it or Grand Central Dispatch

I'm looking for a dataset for my bachelor's thesis, and I need one with lots of variables and observations so I can perform multivariate analysis and predictive modeling. Does anyone know where I could find a geeky dataset related to anime, comics, video games, or anything similar? Any suggestions would be greatly appreciated!

Basically need to see how to optimize a bank register with large amounts of entries.

Currently adding all the debits, then credits, then date sorting while calculating the running total.

Successful replication and matching row counts do not prove that a database migration is finished. Indexes, constraints, sequences, users and roles, collation, time zones, scheduled jobs, change-data-capture consumers, read replicas, analytics tools, and backup systems can still differ or point at the source. Low-frequency clients may not reconnect during the obvious observation window.

A cutover gate could compare schema and security metadata, validate representative aggregates or hashes, exercise application reads and writes, inspect connection logs on both systems, and confirm that replication or dual-write lag has reached a known final position. The destination should complete a backup and restore test and survive a failover before the source becomes read-only. Keeping the old endpoint offline but recoverable for a defined period would expose hidden dependencies without allowing divergent writes.

What evidence do you collect before decommissioning a source database? How do you catch monthly jobs, failover-only connection strings, and clients that cache DNS or credentials longer than the main application?

When one product could have data coming from multiple remote data sources, some of the data could be redundant other parts might need to be combined. There can also be missing data or badly formatted data so an admin would need to override certain fields. How would you structure your database to fit these needs?