Tokyocabinet. Sql. The arrow of time - A short time with MongoDB. I have created a port for FreeBSD 8 for MongoDB but I won't be using it for anything because of these things I found out about it: MongoDB has no, worth repeating: NO provisions for on-disk consistency.
It doesn't fsync, it doesn't use algorithms that would ensure some degree of safety (e.g. journalling), nothing. It does lazy writes! Which means that in case of server or process crashes (which will happen with 100% probability) the whole database could very trivially be corrupted beyond repair. For someone like me who comes from the "real" database world, this makes it unusable.Its performance sucks. Apparently, the developers are willing to work on solving the data consistency issue (which will probably mean they'll have to abandon the pure-mmap approach or at least make very careful use of fsync()s) some time in the future, but I am puzzled by the low performance. 플래시 카페 (Flash,액션,소스,강좌,포토샵,PHP,자바스크립트)
Igvita.com. Anti-RDBMS: A list of distributed key-value stores. Update 8: Introducing MongoDB by Eliot Horowit.
Update 7: The Future of Scalable Databases by Robin Mathew. Update 6: NoSQL : If Only it Was that Easy. BJ Clark lays down the law on which databases are scalable: Tokyo - NO, Redis - NO, Voldemort - YES, MongoDB - Not Yet, Cassandra - Probably, Amazon S3 - YES * 2, MySQL - NO. The real thing to point out is that if you are being held back from making something super awesome because you can’t choose a database, you are doing it wrong.Update 5: Exciting stuff happening in Japan at this Key-Value Storage meeting in Tokyo. Presentations on Groonga, Senna, Lux IO, Tokyo-Cabinet, Tx, repcached, Kai, Cagra, kumofs, ROMA, and Flare. Update 4: NoSQL and the Relational Model: don’t throw the baby out with the bathwater by Matthew Willson. Richard Jones has put together a very nice list of various key-value stores around the internets.
Yet another Key-Value database. Following the NoSQL movement, I became a fan of key-value databases.
Usually there’s nothing interesting to say as they work fine out-of-the-box. But in a project I was recently working on K-V store started to be a major bottleneck. I must note that my use case is pretty specific. In a K-V database I store about ten million records. The keys are pretty small, about 12 bytes on average. I experimented with Berkeley DB and Tokyo Cabinet, but I noticed that both engines do similar things internally. Lux IO - Yet Another Fast Database Manager. Primary Keys: IDs versus GUIDs. Berners-Lee: Semantic Web's success lies in cooperation. Getting Started with Berkeley DB XML.
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