BlogWhy CSV is still king

Why CSV is still king

In the world of data, CSV is the cockroach of file formats. It's simple, resilient, and seemingly impossible to kill off. While flashier formats have come and gone, CSV quietly reigns supreme in the data processing kingdom. But how the hell did this happen? Let's dive into the fascinating history of this accidental standard.

The Accidental Standard

CSV was not invented on purpose. It developed naturally. In the early days of computing, when storage was very limited, programmers needed a simple way to store data in tables. Their solution? Separate values with commas and use a new line for each row. Simple, yet effective.

This approach caught on quickly, spreading across various computing environments:

  • By the 1970s, many business applications were using CSV, from accounting to inventory management systems.
  • IBM included CSV support in its Fortran compiler, making it useful for scientific and engineering applications.
  • CSV wasn't an official standard yet, but it was widely used due to its simplicity and effectiveness.

In the 1980s, spreadsheet programs further popularized CSV:

  • VisiCalc, the first electronic spreadsheet, could import and export CSV files.
  • Lotus 1-2-3 and Microsoft Excel also supported CSV, making it a common format for data exchange.

CSV became crucial for business data. It was used to share financial data, import customer information, and exchange data between different systems. Its simplicity and widespread support made it a universal format for data exchange and a favorite among developers for data tasks.

The rise of the internet and big data brought new opportunities for CSV to shine. Many web services started exporting data in CSV format and accepting CSV imports. Big data systems like Hadoop and Spark embraced CSV for data processing. These developments further cemented CSV's position as a versatile and widely-used data format.

Despite its growing popularity, CSV wasn't without its challenges.

The Problems with CSV

  • No official standard: Leads to inconsistencies in how different software interprets CSV files, despite attempts at standardization like RFC 4180.
  • Text encoding headaches: CSV files don't specify their encoding, potentially causing character misinterpretation, especially with international data or across different operating systems.
  • Tricky comma handling: When data fields contain commas, it can break the CSV structure. Enclosing such fields in quotes is a common but not universally handled solution.
  • The delimiter debate: While commas are most common, the use of tabs (TSV) or semicolons as delimiters remains a topic of ongoing debate in the data community. Each option has its pros and cons, leading to varied preferences across different sectors and use cases.
  • Lack of data type information: CSV files don't inherently carry information about data types, which can lead to misinterpretation of data, especially with dates and numbers.
  • Lack of data structures: CSV is fundamentally a flat file format, making it challenging to represent hierarchical or nested data structures. This limitation becomes particularly apparent when dealing with complex data models or relationships between different data elements.

These problems can make working with CSV files a bit of a pain, especially when dealing with large or complex datasets. However, its simplicity and widespread use have helped it overcome these hurdles.

Why CSV Will Remain King

Given these issues, some predict newer formats like Parquet will replace CSV. Parquet is more efficient for data analysis, but it has a big drawback: you need special software to read it. With CSV, you can use anything from cat to Notepad or Excel.

A JSON variant like NDJSON could be a strong contender since it's plain text based and human-readable-ish, but it's not as widely used as CSV yet.

Here's why CSV will likely stick around:

  • It's good enough for many situations and dead simple to use.
  • Most published datasets today are in CSV format.
  • Many data processing tools still output CSV files.
  • Its human-readability is unmatched among data formats.

Looking ahead, the future of CSV might involve some tweaks:

  • Efforts to standardize it further.
  • New tools to better handle its quirks.

But the core simplicity of CSV will likely keep it relevant for years to come.

So, even though CSV is old and simple, don't underestimate its usefulness. In the ever-changing world of tech, sometimes the simplest solution lasts the longest. CSV is living proof of that, continuing to adapt and thrive in an increasingly complex data landscape.