Data Infrastructure at LinkedIn

Aditya Auradkar, Chavdar Botev, Shirshanka Das, Dave De Maagd, Alex Feinberg, Phanindra Ganti, Lei Gao, Bhaskar Ghosh, Kishore Gopalakrishna, Brendan Harris, Joel Koshy, Kevin Krawez (+24 others)
2012 2012 IEEE 28th International Conference on Data Engineering  
LinkedIn is among the largest social networking sites in the world. As the company has grown, our core data sets and request processing requirements have grown as well. In this paper, we describe a few selected data infrastructure projects at LinkedIn that have helped us accommodate this increasing scale. Most of those projects build on existing open source projects and are themselves available as open source. The projects covered in this paper include: (1) Voldemort: a scalable and fault
more » ... nt key-value store; (2) Databus: a framework for delivering database changes to downstream applications; (3) Espresso: a distributed data store that supports flexible schemas and secondary indexing; (4) Kafka: a scalable and efficient messaging system for collecting various user activity events and log data.
doi:10.1109/icde.2012.147 dblp:conf/icde/AuradkarBDMFGGGGHKKKLNNPPQQRSSSSSSSSTTVWWZZ12 fatcat:4paiys2xcvf3dpgp34gp3skygy