Scaling Derived Data for Planet-Scale Applications at Linkedin

In this video I speak with Felix GV, who is a Principal Staff Engineer at Linkedin, and has done major contributions to the data infrastructure and Linkedin, including VeniceDB. This episode will give you a good understanding of why we need a new database for storing "Derived Data" in a low latency, high performance manner, which is very important for Machine Learning workloads. Chapters: 00:00 Introduction 01:42 The Evolution of LinkedIn's Databases 03:15 Challenges with Voldemort and the Birth of VeniceDB 08:42 Understanding Derived Data 13:33 Planet-Scale Applications and Multi-Region Support 17:40 Writing Data into VeniceDB 22:53 Merging Data in VeniceDB 40:31 Understanding the Architecture 40:47 Components of the Write Path 41:56 Leader and Follower Architecture 43:58 Partitioning and DaVinci Client 47:57 Read Patterns and Client Options 54:25 Fault Tolerance and Recommender Systems 01:01:19 Kafka Integration and Deployment 01:06:56 Roadmap and Future Improvements Important links: VeniceDB blog: https://www.linkedin.com/blog/engineering/open-source/open-sourcing-venice-linkedin-s-derived-data-platform VeniceDB docs: https://venicedb.org/ Qcon: https://youtu.be/pJeg4V3JgYo?si=vblGUxp5fNdKPHoC Follow me on Linkedin and Twitter: https://www.linkedin.com/in/kaivalyaapte/ and https://twitter.com/thegeeknarrator If you like this episode, please hit the like button and share it with your network. Also please subscribe if you haven't yet. Database internals series: https://youtu.be/yV_Zp0Mi3xs Popular playlists: Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA- Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17 Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_d Modern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsN Stay Curios! Keep Learning! #kafka #linkedin #venicedb #Rocksdb