What scalability problems have you solved using a NoSQL data store?
- by knorv
NoSQL refers to non-relational data stores that break with the history of relational databases and ACID guarantees. Popular open source NoSQL data stores include:
Cassandra (tabular, written in Java, used by Facebook, Twitter, Digg, Rackspace, Mahalo and Reddit)
CouchDB (document, written in Erlang, used by Engine Yard and BBC)
Dynomite (key-value, written in C++, used by Powerset)
HBase (key-value, written in Java, used by Bing)
Hypertable (tabular, written in C++, used by Baidu)
Kai (key-value, written in Erlang)
MemcacheDB (key-value, written in C, used by Reddit)
MongoDB (document, written in C++, used by Sourceforge, Github, Electronic Arts and NY Times)
Neo4j (graph, written in Java, used by Swedish Universities)
Project Voldemort (key-value, written in Java, used by LinkedIn)
Redis (key-value, written in C, used by Engine Yard, Github and Craigslist)
Riak (key-value, written in Erlang, used by Comcast and Mochi Media)
Ringo (key-value, written in Erlang, used by Nokia)
Scalaris (key-value, written in Erlang, used by OnScale)
ThruDB (document, written in C++, used by JunkDepot.com)
Tokyo Cabinet/Tokyo Tyrant (key-value, written in C, used by Mixi.jp (Japanese social networking site))
I'd like to know about specific problems you - the SO reader - have solved using data stores and what NoSQL data store you used.
Questions:
What scalability problems have you used NoSQL data stores to solve?
What NoSQL data store did you use?
What database did you use before switching to a NoSQL data store?
I'm looking for first-hand experiences, so please do not answer unless you have that.