是否有稳定且生产质量的 nosql 数据存储?
是否有可以在生产系统上使用的生产质量 nosql 存储。我看过 cassandra、tokyodb、couchdb 等,但它们似乎都没有准备好在生产环境中进行部署。我说的是每分钟数千个请求和大量的读/写/更新。我唯一关心的是速度和服务时间。有人知道有效使用 nosql 存储的生产系统吗?有谁知道有像 Google/Yahoo/IBM 这样的大企业支持的 nosql 商店吗?
Are there are production quality nosql stores that I can use on a production system. I have looked at cassandra, tokyodb, couchdb etc but none of them seem to be ready for deployments on production like environments. I am talking thousands of requests per minute and lots of reads/writes/updates. My only concern is speed and service times. Does anybody know of production systems that use nosql stores effectively ? Does anybody know of a nosql store that is backed by a big enterprise like Google/Yahoo/ IBM ?
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Cassandra 每台机器每秒处理数千个请求(包括主要是写入的工作负载),并且从第一天起就通过添加机器进行扩展。
这是一个关于 Cassandra 在生产中使用的主题并很快在数十家公司投入生产:http://n2. nabble.com/Cassandra-users-survey-td4040068.html#a4040068
我们还一直在添加更多文档,例如 http://wiki.apache.org/cassandra/Operations。
Cassandra handles thousands of requests (including write-mostly workloads) per second, per machine, and its scaling-by-adding-machines has been there since day 1.
Here is a thread about Cassandra use in production and in-production-soon at dozens of companies: http://n2.nabble.com/Cassandra-users-survey-td4040068.html#a4040068
We're also adding more docs all the time, like http://wiki.apache.org/cassandra/Operations.
我认为,如果我“只”关心速度和服务时间(而不关心或不太关心一致性和事务等内容),NoSQL 系统是一个很好的选择。 Facebook 使用 Cassandra。
“Cassandra 在 Facebook 中用作电子邮件搜索系统,包含 25TB 和超过 1 亿个邮箱。” http://highscalability.com/product-facebooks-cassandra-massive-distributed- store
我认为 CouchDb 并不是很快,也许你可以使用 MongoDB: http://www.mongodb.org/display/DOCS/Production+Deployments
I think the NoSQL systems are an excellent choice if I you 'only' care about speed and service time (and not or less about stuff like consistency and transactions). Facebook uses Cassandra.
"Cassandra is used in Facebook as an email search system containing 25TB and over 100m mailboxes." http://highscalability.com/product-facebooks-cassandra-massive-distributed-store
I think CouchDb isn't really speedy, maybe you can use MongoDB: http://www.mongodb.org/display/DOCS/Production+Deployments
另外值得考虑的是使用 MySQL 等传统 RDBMS 来存储无模式。此方法为您提供 MySQL 等经过验证的数据库服务器的稳定性以及 NoSQL 解决方案的灵活性。
查看此博客文章,了解如何FriendFeed 就是这样做的。
Also worth consideration is using a traditional RDBMS like MySQL to store schema-less. This method gives you the stability of a proven database server like MySQL with the flexibility a NoSQL solution.
Check out this blog posting on how FriendFeed does this.
BerkeleyDB 由 Oracle 支持
使用本机 C 接口,可以接近每秒 100 万个读取请求。
顺便说一句,当您说每分钟数千个请求时,任何“普通”数据库也应该能够轻松处理。
BerkeleyDB is backed by Oracle
Using the native C interface one can reach close to 1 million read requests per second.
By the way, when you say thousands requests per minute, any 'normal' DB should be able to handle that easily too.
Redis 值得一试,因为 Github 使用 redis 来管理 的繁重队列后台作业。
Redis is worth giving a try as Github uses redis to manage a heavy queue of background jobs.
我的第一反应是 BerkeleyDB,每个应用程序节点都位于 SAMBA 网络上,以促进 ACID 一致性和一致性。网络使用。它还具有 SQLite 界面。其他海报引用 MemcacheDB 内部也有 BDB。
另一个独特的选择是 OrientDB,它也有一个 SQL 接口、大量的网络和数据。集群特征。
My first instinct would be BerkeleyDB, with each application node on a SAMBA network to facilitate ACID conformance & network use. It also sports a SQLite interface. Other poster cites MemcacheDB also having BDB inside.
Another unique option would be
OrientDB
, also has a SQL interface, lots of network & cluster features.