Go in Data Engineering: A Journey Through the 5 Vs and harnessing the Power of Go

For old school Data Engineers, the 5 Vs — value, volume, velocity, veracity, and variety — are pillars shaping data platforms and systems. But as we continue to improve our systems and move to cheap storage ecosystems — like the cloud, Data engineers need tools that offer speed, reliability, and scalability. This is where Go (Golang) emerges as a game-changer, empowering data engineers to conquer the challenges posed by the 5 Vs with finesse.

Gophers based on the original design of Renee French. Artist Connor Searing

Value

Data engineering strives to provide valuable data. Data value is enhanced by data transformations. Go’s performance prowess ensures that data processing tasks are executed swiftly and efficiently, maximizing the value derived from every dataset.

Volume

Handling massive volumes of data is a given. Go’s compiled nature and lightweight concurrency mechanisms enable it to easily handle large-scale data processing, ensuring optimal performance even with vast datasets. Go is quicker than Python because it is compiled into a low-level language.

Velocity

Every data practitioner wants their data faster. We are always moving to make data systems more real-time. Go’s built-in concurrency features, such as goroutines and channels…