It is amazing to see the number of projects based on Postgres mentioning that they are trying to achieve multi-master with their own restrictions: * Postgres-R

It is amazing to see the number of projects based on Postgres mentioning that they are trying to achieve multi-master with their own restrictions: * Postgres-R is not multi-master, got discontinued in 2010, and lots most of its meaning after WAL-shipping has been added in-core with hot-standby. http://www.postgres-r.org/ http://www.postgres-r.org/ * Postgres-XC, that says to do multi-master, the first project based on PostgreSQL that I heard of doing sharding (term not used at the beginning of the project, and that I first heard in 2010). The project began in 2009, got discontinued in 2013. There are limitations like non-support for triggers and savepoints. XC was designed to be good for OLTP workloads, sucks for long-transactions and data warehouse type of workloads. The design of the project has been done in coordination by NTT and EnterpriseDB. https://sourceforge.net/projects/postgres-xc/ https://sourceforge.net/projects/postgres-xc/ * Postgres-XL, that forked from Postgres-XC, and enhanced the data-warehouse case with improvements for data analytics by introducing a communication protocol between Datanodes. The project is still being maintained by some folks at 2ndQuad. http://www.postgres-xl.org/ http://www.postgres-xl.org/ * Postgres-X2, which has been an attempt to unify Postgres-XC and Postgres-XL efforts under the same banner. I don't know where this is moving to but things look rather stalled. https://github.com/postgres-x2/postgres-x2 https://github.com/postgres-x2/postgres-x2 * Postgres-XZ (look for PGXZ!), which is something I heard recently, based on Postgres-XC, and developed by some folks in China. Visibly this has its own limitations, and is used in production where the constraints induced by the scaling out are thought as acceptable. So, that's cool to see many efforts, BDR being one. And all of them are trying to address the scaling-out problem with their own way. Now each application should study carefully what to use and if the limitations and constraints used are acceptable or not.