Databases vs. Flat Files – Lecture Review

These flashcards cover key concepts, history, terminology, and comparative strengths and weaknesses of flat files and relational databases discussed in the lecture.

What is a flat file database?

A simple database that stores all data in a single table with no indexes, keys, or relationships between rows.

What is a delimiter in the context of flat files?

A sequence of one or more characters (e.g., comma or semicolon) that marks the boundary between fields in plain-text data.

Why do flat files become difficult to manage as the volume of data grows?

Because queries are slow without indexes, redundancy increases storage needs, and there are no built-in relationships to organize the data.

Who introduced the relational database model and in what year?

British computer scientist Edgar Codd in 1970.

Which language did IBM develop to interact with relational databases?

SQL (Structured Query Language).

Why was Oracle’s 1979 release significant?

It was one of the first commercial relational database products and helped popularize the relational model.

List three advantages relational databases have over flat files.

Greater efficiency in storage/retrieval, better scalability (can be partitioned across servers), and flexibility through support for complex relationships.

How do relational databases reduce data redundancy?

By storing each piece of data once in its own table and linking related tables through keys.

What is a spreadsheet, in database terminology?

A row-and-column grid application (e.g., Excel) often used as a modern form of a flat file.

Name two pioneering spreadsheet programs from the late 1970s–early 1980s.

Visicalc (1979) and Lotus 1-2-3 (1983).

State four common weaknesses of flat files.

Data redundancy, increased security risk, potential data inconsistency, and limited flexibility/expandability.

How can data inconsistency arise in flat files?

Multiple copies of the same data may diverge if they are updated or entered incorrectly in different rows or files.

What is a NoSQL flat file database and give a popular example.

A database that stores unstructured or semi-structured data (often key-value pairs); MongoDB is a leading example.

In a relational database example, what column links the invoice and customer tables?

customer_id.

Why would a company like Amazon struggle using a single-table flat file?

The table would become enormous, highly redundant, and too slow and costly to process.

What role do indexes play in relational databases?

They speed up queries by enabling rapid lookup of rows that match specific criteria.

Before computerized databases, how were records typically organized?

As physical ledgers in file folders and filing cabinets, resembling today’s flat-file ‘boxes’ and ‘cards.’

What database-related idea did John Backus propose in 1959?

A specialized database and programming language to improve data retrieval for computers.

When might a NoSQL database be preferred over a relational one?

When very fast read/write operations or storage of unstructured/semi-structured data is required.

Define data redundancy.

The unnecessary duplication of the same data within or across files, wasting space and risking inconsistencies.

What key security limitation do flat files have?

They rely on operating-system file permissions, and multiple redundant copies increase exposure to unauthorized access.

Why are relational databases considered more scalable than flat files?

They can partition data across multiple servers and efficiently manage large datasets with indexes and optimized storage structures.

What is the purpose of a delimiter?

To indicate where one field ends and the next begins in a plain-text data stream.

What drove the evolution from flat files to relational databases?

The need for more efficient, scalable storage and the ability to perform complex queries on related data.

Give three common applications that rely on relational databases.

Enterprise Resource Planning (ERP) systems, Customer Relationship Management (CRM) systems, and data warehouses.