商业智能和 NoSQL
对于我正在工作的新项目，我需要将一些数据存储到数据库中。数据类型和访问模型非常适合 NoSQL 模型和文档数据库。我们正在考虑 MongoDB 之类的东西，但尚未决定。
要求之一是能够允许商业智能工具使用我们的一些数据。我工作的其他人表示这些工具允许直接使用关系数据库中的数据。我不知道需要什么类型的商业智能工具来挖掘数据。
BI 工具通常也支持非 SQL 数据库吗？他们是否还有其他可能适用的标准集成选项（有些似乎支持平面文件的 Web 服务）？是否值得仅仅为了让第三方 BI 工具更容易使用而选择关系数据库？
For a new project I'm working I have the need to store some data into a database. The type of data and access model fits well with the NoSQL model and document databases. We are considering things like MongoDB but are still yet undecided.
One of the requirements is to be able to allows Business Intelligence tools to consume some of our data. Others I work for indicate that these tools allow consuming data directly from relational databases. I know not know what types of Business Intelligence tools need to mine the data.
Do BI tools typically support non-SQL databases as well? Are there other standard integration options that they have (Some seem to support web services of flat files) that might be applicable? Is it worth choosing a relational database simply so it can be more easily consumed by a third party BI tool?
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不，他们真的不能。非 SQL 数据库彼此之间有很大不同。 NoSQL 实际上只是一组松散的“非 SQL 的东西”。
然而，您将面临的问题是一个经典问题。大多数 NoSQL 数据库的运行理念是您可以“批量”和“输出”您计划执行的报告。 （通常这意味着映射减少）
因此，如果您想使用常见的 BI 工具，您只需“弥合差距”。
MongoDB 支持 CSV 导出，然后可以将其导入到关系数据库中进行分析。对于某些复杂的查询，您可能需要编写“map-reduce”查询，然后导出该数据。显然，您必须编写几个导出/导入脚本。
但很有可能提供 BI 报告并仍然使用 MongoDB 作为数据的主要存储。您仍然需要为 BI 套件运行 RDBMS。但它不太可能需要太多硬件，因为它仅用于报告而不是实时数据。
No. And they really can't. Non-SQL databases are very different from each other. NoSQL is really just a loose set of "things not SQL".
However, the problem you're going to face is a classic one. Most NoSQL database are run under the concept that you can "batch" and "output" the reporting that you're planning to do. (typically this means map-reduce)
So if you want to use common BI tools, you simply have to "bridge the gap".
MongoDB supports a CSV export that can then be imported into a relational DB for analysis. For some complex queries, you'll likely need to write "map-reduce" queries and then export that data. Obviously, you'll have to write a couple of export / import scripts.
But it's quite possible to provide BI reporting and still use MongoDB as the primary store of data. You'll still need an RDBMS running for the BI suite. But it's unlikely to require much hardware as it's just used for reporting and not for live data.
MongoDB 非常好，但不够灵活。开发人员在开发应用程序时定义实体之间的关系。然而，商业智能意味着具有领域知识的人可以寻找实体之间的新关系。数据可以获得开发人员开发表/集合结构时未知的新含义。
MongoDB is very nice but it isn't flexible. The developer defines the relations between the entities when developing the application. However business intellegence means that people with domain knowledge can look for new relations between entities. Data can get new meaning that was unknown when the developer developed the structure of the tables/collections.
自从这个问题提出 10 年来，BI 领域已经发生了很多变化。 BI 工具通过将 json 响应展平为行格式来从 MongoDB 数据源读取数据。
Since 10 years this question was raised, a lot has changed in the BI landscape. BI tools do read from MongoDB data source by flattening the json response into a row format.