I learned my software skills on the Ferranti Mercury computer. It had as I recall 468 words of memory (a word is about 6 bytes so call it 3k bytes). Let's see, my phone has 8,000,000,000 bytes - that's about 2.5 million times more. My phone makes the 1500 instructions per second look pretty silly as well.
The computer was big. The electronics used valves and they get hot. So each cabinet has a refrigerating unit built-in, and they were noisy.
When we all got locked down, I needed a project to keep my brain active. (That gets important as you get older: I just had my 80th birthday). My wife is learning Spanish and I tried writing a novel (it didn't fly). In the end I decided to do something that I was good at - software development. I wrote a generic system to update and query a database using node.js. Test system here: http://www.sudsjs.com.
The database is accessed through a driver, which initially was written and tested for MySL, PostgreSQL and SQLite 3. I downloaded Oracle (XE) but it turned out to be a pain to install in Ubuntu, so I put it on the backburner.
Since then, I have implemented (or tried) various NOSQL systems. So here is a summary and a link to any blog posts about all of the databases I have used. I will update this post as I look at different systems.
I decided to use my lockdown project SUDSJS.com to test out a few different NOSQL database management systems (DBMS).
SUDSJS is written in JavaScript using the node.js server-side system and I designed it so that I could plug in different drivers for different databases. I wrote database drivers for MySQL, SQLite 3 and PostgreSQL. The first NOSQL system I tried was MongoDB, and the SUDSJS.com test site is currently running using this. The second NOSQL system I tried was Firestore from Google.
It didn't go well.
You know what an invoice looks like. We have all seen thousands of them - probably too many. But invoices illustrate an interesting problem - and I am not talking about your VAT return. I am talking about the new kids on the database block - document databases. An example is MongoDB. These can store all the data for one invoice in a single structured record (called a 'document').
In a traditional Relational Database, the data is held in flat tables, like big spreadsheets. Invoices will be stored in two tables, one for information about the invoice, like customer and date (call it the 'invoice header'). The second table will store all the invoice lines. One row per line. The lines will be linked back to their invoice by an invoice number. But what happens if the invoice header disappears, but the invoice lines are still there?
