IT Hare on Soft.ware
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System Architecture (and it’s subfield Software Architecture) is a discipline which is surprisingly poorly covered. In a sense, it is still more an art than a science, and usually requires somebody intimately familiar with practical systems, to tell what’s to do and what’s to avoid when building a system.

IT Hares have lots of experience in both Software Architecture and more general System Architecture, and are trying to share their knowledge (and more importantly, their feelings) about them.

All Not so Common Wisdoms about System Architecture, page 3:

Gradual OLTP DB Development – from Zero to 10 Billion Transactions per Year and Beyond

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Quote: “to make an efficient representation usable for OLAP – we need to modify our data on its way to OLAP replicas”
Another Quote: “Each of the DB Server Apps is a replica master, but all replica targets are within the same Replica DB”
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Representing The Same Data Structure in SQL and NoSQL (from Classical Codd-style SQL to Key-Value NoSQL with SQL-with-XML and Structured NoSQL in between)

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Quote: “while duplication MAY indeed improve performance – undue duplication also MAY hit performance pretty badly”
Another Quote: “NoSQL will usually call for another denormalisation on top of what we’ve described above for SQL-with-XML.”
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OLTP. Compiling SQL Bindings.

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Quote: “If we’re speaking about millions transactions per day over just a few hundred of different SQL statements – compiling those statements a million times (instead of a few hundred times) will be a dramatic waste of resources.”
Another Quote: “Once upon a time, I observed the largest C++ file in my career – it was a 30’000-line file(!) consisting merely of ODBC bindings (and that was just for 300 or so SQL statements)”
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Historical Data in Databases. Audit Tables. Event Sourcing

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Quote: “99% of reporting requests and 99.9% of analytics is purely historical”
Another Quote: “Information within the audit table should be sufficient to validate/justify current state”
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Ultimate DB Heresy: Single Writing DB Connection. Part II. Gradual Scalability. All the way from no-scale to perfect-scale.

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Quote: “And after this split of USERS table, the system has achieved perfectly linear scalability.”
Another Quote: “Start with a simple single-write-connection DB, with reporting running off the same DB”
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Ultimate DB Heresy: Single Modifying DB Connection. Part I. Performance (Part II. Scalability to follow)

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Quote: “Dealing with transaction isolation is very far from being a picnic”
Another Quote: “One of such real-world systems was consistently processing over 30M real-world write transactions/day over one single DB connection, supporting ~100K simultaneous players.”
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