大数据-存储和查询 [英] Large data - storage and query

问题描述

我们有大约 3 亿条记录的庞大数据，每 3-6 个月会更新一次.我们需要(连续、实时)查询这些数据以获取一些信息.有哪些选项 - 一个 RDBMS(mysql) ，或者其他一些选择，比如 Hadoop.哪个会更好?

We have a huge data of about 300 million records, which will get updated every 3-6 months.We need to query this data(continously, real time) to get some information.What are the options - a RDBMS(mysql) , or some other option like Hadoop.Which will be better?

推荐答案

300M 记录完全在常规关系数据库的范围内，如果您正确使用索引，实时查询应该没有问题.

300M records is well within the bounds of regular relational databases and live querying should be no problem if you use indexes properly.

Hadoop 听起来有点矫枉过正，除非您真的需要高度分布式和冗余的数据，而且如果您遇到问题或需要优化，它也会让您更难找到支持.

Hadoop sounds like overkill unless you really need highly distributed and redundant data, and it will also make it harder to find support if you run into trouble or for optimizations.

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