Headache-free stored objects: a simple example of working with InterSystems Caché objects in ObjectScript and Python

Neuschwanstein Castle

Tabular data storages based on what is formally known as the relational data model will be celebrating their 50th anniversary in June 2020. Here is an official document – that very famous article. Many thanks for it to Doctor Edgar Frank Codd. By the way, the relational data model is on the list of the most important global innovations of the past 100 years published by Forbes.

On the other hand, oddly enough, Codd viewed relational databases and SQL as a distorted implementation of his theory. For general guidance, he created 12 rules that any relational database management system must comply with (there are actually 13 rules). Honestly speaking, there is zero DBMS's on the market that observes at least Rule 0. Therefore, no one can call their DBMS 100% relational :) If you know any exceptions, please let me know.

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Sometimes global mapping of the same globals can be defined in different ways. E.g., I need to define it for 3 globals ^qAuditC, ^qAuditLog, ^qAuditLogC from the same database named APP-NOJOURN. Which approach should be better from the performance point of view?

1) qAudit* => APP-NOJOURN (one record in global mapping table)
or

2) qAuditC => APP-NOJOURN
qAuditLog => APP-NOJOURN
qAuditLogC => APP-NOJOURN (three records in global mapping table)

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Article
· Mar 31, 2019 20m read
How to write the home address right?

How Tax Service, OpenStreetMap, and InterSystems IRIS
could help developers get clean addresses

Pieter Brueghel the Younger, Paying the Tax (The Tax Collector), 1640

In my previous article, we just skimmed the surface of objects. Let's continue our reconnaissance. Today's topic is a tough one. It's not quite BIG DATA, but it's still the data not easy to work with: we're talking about fairly large amounts of data. It won't all fit into RAM at once, and some of it won't even fit on the drive (not due to lack of space, but because there's a lot of junk). The name of our subject is FIAS DB: the Federal Information Address System database - the databases of addresses in Russia. The archive is 5.5 GB. And it's a compressed XML file. After extraction, it will be a full 53 GB (set aside 110 GB for extraction). And when you start to parse and convert it, that 110 GB won't be enough. There won't be enough RAM either.

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Hi, we are a veterinary lab and we use both the LAB and FIN systems of Antrim. Now we are looking to expose the data in a SQL/Object compatible way so we were wondering if same / similar things had been done by other community members already? If so, could you please share your approach / experience / gotchas with us and we are all ears. I can be reached at yang.jiao@antechmail.com . Thank you!

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