Apache Spark Vs Apache Flink – Looking Through How Different Companies Approach Spark And Flink

As data increased in volume, velocity, and variety, so, in turn, did the need for tools that could help process and manage those larger data sets coming at us at ever faster speeds. As a result, frameworks such as Apache Spark and Apache Flink became popular due to their abilities to handle big data processing in a fast, efficient, and scalable manner. But we often find that sometimes it can be difficult to understand which use cases are best suited for Spark as well as for Flink (or even which might be suited for both). In this article, we’ll discuss some of those unique benefits for both Spark and Flink and help you understand the difference between the two, and go over real use cases, including ones where the engineers were trying to decide between Spark vs. Flink. Also, thank you to the sponsor for this video Deltastream, you can try them out for free here - https://www.deltastream.io/trial/?utm_source=sdg&utm_medium=video If you enjoyed this video, check out some of my other top videos. Top Courses To Become A Data Engineer In 2022 https://www.youtube.com/watch?v=kW8_l57w74g What Is The Modern Data Stack - Intro To Data Infrastructure Part 1 https://www.youtube.com/watch?v=-ClWgwC0Sbw If you would like to learn more about data engineering, then check out Googles GCP certificate https://bit.ly/3NQVn7V If you'd like to read up on my updates about the data field, then you can sign up for our newsletter here. https://seattledataguy.substack.com/​​ Or check out my blog https://www.theseattledataguy.com/ And if you want to support the channel, then you can become a paid member of my newsletter https://seattledataguy.substack.com/subscribe Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio _____________________________________________________________ Subscribe: https://www.youtube.com/channel/UCmLGJ3VYBcfRaWbP6JLJcpA?sub_confirmation=1 _____________________________________________________________ About me: I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data. *I do participate in affiliate programs, if a link has an "*" by it, then I may receive a small portion of the proceeds at no extra cost to you.