Who invented csv

IBM and General Electric invented the first databases in the early s. It was only by the early s that enough data had accumulated in databases that the need to transfer data between databases emerged.

Dump the contents of a table to a CSV, import it into another database. Sound familiar? That's because it's still the most common method of data distribution today. We have large corporations, academia, and government all distributing data on the internet in CSV format. Almost 50 years after invention CSV remains the standard for data exchange.

The next innovation in data exchange happened in the early days of the internet. On the internet, we were not exchanging whole tables of information. We had lightweight connected applications that needed access to single or few records to render to users. We needed a data format that could be transmitted via Application Programming Interfaces APIs , the data exchange layer of the internet. The ideal data exchange format used in APIs would represent small collections of information, potentially with hierarchical information.

For example, we needed to be able to ship an object with a variable length list of tags associated with it. We did not want to make two API calls, one for the base object and one for the list of tags as it would be structured in a relational database. XML quickly went out of favor, mostly because of verbosity. The tags were often larger than the data payload. JSON was far less verbose but could only represent key-value pairs and arrays. There are now thousands of public and private APIs to facilitate all manner of data exchange on the internet.

APIs are the middleware of the internet. However, we're in the midst of a generational shift in the way software is written, Software 2. It turns out that a large portion of real-world problems have the property that it is significantly easier to collect the data or more generally, identify a desirable behavior than to explicitly write the program. For example, what if there is a comma in a value?

You could encapsulate the value in double quotes, but what if the quote characters are also inside that value? What if the character used to delineate records ie, a newline is present within the data?

What if your file uses a character other than a comma to delineate values? And so on. The answers to these questions are often ad hoc and system dependent, so depending on where the CSV data you're working with came from, you need to apply a different set of rules in order to properly interpret that data. If you're lucky, your source system provides thorough documentation.

CSV has been in use since the s, but it is not standardized. While this may be a useful reference, there is no guarantee a file that a system you're working with calls a "CSV" file follows this RFC. For example, Microsoft Excel explicitly does not. The RFC itself states this:. The Library of Congress provides a more "real-world" definition of CSV and describes many common deviations:.

I've seen most or all of these deviations in practice. You may want to look into the documentation for the specific CSV writer or parser that you're working with, if it exists, to understand how that individual system handles CSV. Some systems will handle CSV relatively well, while others may fail in inscrutable ways. If you're working with CSV-formatted data, you may want to transform your CSV data and load it into a different system which has different expectations for how a CSV is formatted.

You also may want to load data from a CSV and perform transformations and analytics on it. Here are a number of tools that I find useful when working with CSV files. Most of these tools assume you have some experience with the command line and installing software from a binary or package repository. It can do a number of simple operations, including slicing data, sorting data, performing basic analytics, reformatting CSV data, fixing mis-matched rows, etc.

Check out the documentation for more information. If you're doing more complex analytics or transformations on your data, xsv may not be appropriate and you may want to look into some of the other tools below.

It serves a similar role, but is not nearly as fast. This is a good library to use if you need to do something XSV can't do or if you're working with smaller files and performance isn't as important. Most relational databases have the ability to import or export from CSVs. This is a great strategy for doing complex analytics on large datasets with relatively good performance. It's also easy if you're already familiar with SQL.

I recommend SQLite for doing analytics like this, as it doesn't require a server and can write directly to disk or even run in memory, but you could also use another relational database that you're more familiar with. There are some notable similarities between CSV and Excel files.

For instance, both formats help store data in a tabular format, can be opened in spreadsheet programs, and manipulated using the functions and features found in excel. Users rely on these formats depending on their needs. There are services that only CSV can deliver regardless of how inferior the format may appear. However, if we are to come up with an outright winner, JSON has to be up there.

The format is fast, secure, and convenient. About the Author. Digital transformation through technologies such as automation, the internet of things IoT , and cloud computing, increases the chances of data leaks and security breaches.

Computer programmers are all singing-all dancing technical wizards. They understand the importance of computer resources to deliver accurate and efficient results. A computer monitor is Advantages How does it help businesses? In a nutshell, the following are the most important rules defining the structure of this format: Each new record is delimited by a line break CRLF i. It is expected that this record would consist of the same numbers of fields as the other records.

Why CSV is still used so widely? Advantages The advantage of using the CSV files ultimately boils down to the specific use case. CSV is easy to create. As CSV format is human-readable, it is easy to create.

CSV is human readable i. This increases the readability as well as the ease of manipulation. Moreover, it is easy to edit. CSV files can be read using almost any text editor. It is easy to parse. CSV format is dictated by a straightforward schema. The advantage of having a simple schema makes it a popular choice for number crunching works. Manipulating the CSV file is fast. Due to the simple nature of this format, it is less taxing for the parser to parse the data.

Hence, it results in swift data read and write. While the CSV format is usually not known for its memory efficiency, it, in general, results in small files.

That being said, many other formats available out there provide more memory savings than CSV. CSV format is compact.

You need to start and end tags separately for each row and column which can be unwieldy. How does it help businesses? What is a CSV file and how do I open it? How do you create a CSV file? With regards to scalability, JSON has the upper hand with regards to adding and editing content. CSV seems to be lagging behind a little bit.