Data Storage: JSON vs. CSV

While the above definitions explain JSON and CSV in their briefest form, let's take a closer look at these file types. This article will compare JSON and CSV, provide explanations of both formats, and briefly explain the XML format.

What is JSON?

JSON is a data exchange format that stands for JavaScript Object Notation. JSON is known as a light-weight format type and is favored for its readability and nesting features. It is often used in conjunction with APIs and data configuration. More specifically, JSON is preferred for API use, which prioritizes file size due to its lightweight feature. JSON is also praised for its ability to be easily converted into other formats. JSON conversion tools are quite common, and there are many free JSON to CSV format conversion tools out there.

Additionally, because JSON is derived from the commonly used JavaScript programming language, it can be easily integrated into front-end and back-end development. JSON files (.json), unlike CSV, which will be discussed later on, have immense nesting and hierarchy features due to its syntax. To further illustrate this, let’s take a look at the data types (elements) that JSON supports.

JSON data types

Here are some of the data types that JSON uses include:

• Strings: “Blue” “Lukas” “Orange Juice”
• A string is a sequence of characters that can be a constant or a variable. Strings in complex computer languages and data storage types are usually words.
• Numbers: “55” “-2.5” “3.5e10”
• A number in a string of JSON data can exist as an integer, decimal number, negative number, or even scientific notation numbers.
• Booleans: “True” “False”
• A boolean represents data whose value exists as true or false.
• Null: “null”
• Null is another term for “nothing” and communicates that an input has no value.
• Array: [55,56,57] [“Blue”, “Purple”, “Green”]
• Arrays are lists that can include any of the above-mentioned types as well as objects (below).
• Objects: {“key”: “value”} {“name”: “Lukas”}
• Objects are the most commonly used data types, and allow you to represent values that are key-value pairs. You can assign data a key and a value, where the value can be any of the above-mentioned data types (string, number, null, etc.).

What does JSON look like?

Now that we know the elements that JSON supports, let’s look at data represented in the JSON format. For consistency, we will look at JSON, CSV, and XML with the same sample data. This sample data will be for some company “X” with two employees - Jane and Lukas.

{“name”:”Jane”,”jobTitle”:”Analyst”}

{“name”:”Lukas”,”jobTitle”:”Developer”}

And now, let’s continue to CSV. First, let’s see how CSV compares to JSON.

What is CSV?

CSV is a data storage format that stands for Comma Separated Values. Implied in its name, CSV stores the data (values) in a list format separated by commas. CSV is noted for its small file size and simplicity. Likewise, because of its simplicity, CSV can be used by virtually anyone who is tasked with examining simple data in spreadsheets and tables. CSV files can be converted to JSON format, but complex JSON files may lead to reading and writing errors.

However, CSV files pose a few obstacles, especially when dealing with files whose data entries are large in quantity. To further illustrate this, let’s examine CSV’s data type.

CSV and tabular data

Typically, CSV files (.csv) tend to store tabular data (numbers and text) in plain text. While CSV can store other types of data besides tabular data, doing so adds unnecessary complexity to the file, decreases the readability, and increases room for error when writing.

CSV files and tabular data consist of columns and rows of numerical and textual data all separated by commas. The first line of text in a CSV file contains all of the headers (columns) corresponding to other values in the file. The other lines of text (rows) contain either numbers or text, separated by commas to indicate which header column it corresponds to.

As you can imagine, CSV data opened in a plain text editor is challenging to read, especially if the CSV file contains hundreds or thousands of data entries. Additionally, CSV files are not always accessible internationally as commas and periods have different meanings, such as commas equating to decimal points in many European countries. This is also why many CSV files use semicolons instead of commas to separate elements.

What does CSV look like?

Here’s a simple example of how CSV data might look like:

Name, Job title

Jane, Analyst

Lukas, Developer

XML vs CSV

XML stands for eXtensible Markup Language and is another widely used standardized data storage format. XML is a markup language on a more technical level, which means it has a process for annotating data in a syntactically significant way. While XML was initially designed for documents, XML is now primarily used to represent complex data structures seen in web services such as APIs.

What does XML look like?

Here’s an example of what XML data looks like:

<person>

<name><br />

Jane<br />

<name/>

<jobTitle><br />

Analyst<br />

<jobTitle/>

<person/>

<person>

<name><br />

Lukas<br />

<name/>

<jobTitle><br />

Developer<br />

<jobTitle/>

<person/>

What are the pros and cons of XML?

Pros of XML

• Fully supports hierarchical data structures
• Most browsers have XML readers that enable XML file inspection
• Works with nearly all APIs, especially older APIs
• Can handle large amounts of syntactically significant data

Cons of XML

• XML has a considerable file size (about three times larger than the CSV format)
• More complex in syntax than JSON (requires opening and closing parameter tags for each element)
• Not as simple as JSON

The importance of data storage

Now more than ever, companies rely on data to reach their business goals. With the ever-expanding data landscape, understanding data storage is necessary for professionals working in data-driven businesses. Finance and investment decisions are overwhelmingly guided by data; however, not all data comes in the same format. There are many benefits to harnessing the different data storage formats and using each one in ways that will maximize their respective properties.

For instance, investment analysts utilize alternative data, which often comes in many different formats, to begin with. Additionally, datasets used by analysts, developers, and investors alike are usually massive in scale. On the other hand, datasets used internally or for specific projects may be much smaller and may not require complex syntax.

Choosing the right data storage format for your business needs is a paramount decision. The good news is that there are many useful, standardized formats to choose from. The standardization of data formats is important because it allows easy data parsing. While there are three main standardized data exchange formats to choose from, JSON,  CSV, and XML, understanding the benefits and shortcomings of each will provide clarity on which format works best for you.

Summary

In a data-driven world, it is important that you choose the right data storage format for your business needs. Between JSON, CSV, and XML, you are likely to find a format that meets your data needs, and in some cases, you may utilize more than one format. Coresignal provides you with data solutions in JSON file formats, allowing easy data parsing. Ultimately, understanding all facets of data, how it is used, how it is stored, etc. will unlock many opportunities for your company.