Facebook is one of the biggest companies who open sourced some of its projects. In this article, we will talk about three of them. 3 biggest Facebook’s open source projects are React, Presto and Rocks DB.
React is used as the View in MVC architecture. React abstracts away the DOM from you, giving a simpler programming model and better performance.
Facebook open sourced React in May 2013, and in the past year, we’ve continued to see strong collaboration in the community, including a 75% increase in the number of commits and a 198% increase in the number of forks.
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. A single Presto query can combine data from multiple sources, allowing for analytics across your entire organization.
Presto is available to others since November 2013, we’ve seen a lot of growth, adoption, and support for it, including a 48% increase in the number of commits and a 99% increase in the number of forks in the past year. Companies like Airbnb, Dropbox, and Netflix use Presto as their interactive querying engine. We also see growing adoption all over the world, including by Gree, a Japanese social media game development company, and Chinese e-commerce company JD.com.
RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads.
RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.
RocksDB was open sourced in November 2013. Aside from the impressive 52% increase in the number of commits and the 57% increase in the number of forks for this project in the past year, the reason this particular project has resonated so well in the open source community is that the embedded database helps provide a way to work around slow query response time due to network latency, and it is flexible enough to be customized for various emerging hardware trends.