The main insight is that traditional data processing focused on storing data and batch processing, where data was processed periodically. However, with the rise of complex software systems consisting of multiple pieces of software with their own data, the focus shifted to real-time processing of data streams to react to events as they happen. This real-time processing of data streams was seen as a natural generalization of database ideas, and while it was previously considered research-oriented, the insights led to the development of a project internally at LinkedIn and its subsequent open-sourcing to the rest of the world.

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode