SQL, or Structured Query Language, is a language designed specifically for communicating with databases. SQL databases, also known as relational databases, have been a prevailing technology for over four decades. They organize data into one or more tables, each with a unique key identifying every record.

An SQL database functions on the principles of ACID (Atomicity, Consistency, Isolation, Durability). ACID compliance reduces anomalies and protects the integrity of your database by prescribing exactly how transactions interact with the database. This is particularly helpful in sectors such as finance where consistency of data is paramount.

SQL databases support complex querying, thus allowing intricate filtering within the data. This makes SQL databases suitable for applications where complex transactions are involved. This might actually ring a bell to our AI enthusiasts who frequently need to handle complex numerical datasets.

The Python code given as an example demonstrates a basic transaction using Python’s sqlite3 module, a light-weight disk-based database, well suited for testing and prototyping. Here, a table named 'stocks' is created, a record is inserted, and then we query all records, ordered by the price.

SQL databases require a fixed schema defining the data structure before you can store anything. This feature ensures the necessary rigidity for applications that need consistent data, building the foundation for a strong, predictable model. This is particularly relevant in traditional client-server applications where consistency is key.

In conclusion, SQL databases prove a good choice when the problem domain is well understood, and if strong consistency in data is required. They are an excellent choice for applications involving complex transactions, or for analytics solutions requiring complex querying.

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if __name__ == "__main__":

  # Python logic here

  # For instance, this is how a typical transaction could be implemented using Python’s sqlite3 module

  import sqlite3

​

  conn = sqlite3.connect(':memory:')

  c = conn.cursor()

  c.execute('''CREATE TABLE stocks (date text, trans text, symbol text, qty real, price real)''')

​

  # Insert a row of data

  c.execute("INSERT INTO stocks VALUES ('2006-01-05','BUY','RHAT',100,35.14)")

​

  # To save the changes

  conn.commit()

​

  # Do some operations with the data

  for row in c.execute('SELECT * FROM stocks ORDER BY price'):

    print(row)

​

  conn.close()

​

  print("This is how a basic SQL database operation using python looks like.")