RDF存储与传统数据库的性能比较
有人尝试过像 Sesame 这样的 RDF 存储解决方案吗？ 我正在寻找与传统数据库解决方案相比的此类解决方案的性能审查。
Has someone experiment RDF storage solution like Sesame? I'm looking for performance review of this kind of solution compared to the traditional database solution.
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我在工作项目中广泛使用了芝麻。 我发现它对于我所处的大多数情况来说都足够快速和可靠。它在各个方面都明显优于耶拿的存储解决方案。 Sesame 1.x 的查询性能比 2.x 版本更快，但 2.x 版本有一些不错的功能，例如上下文和 sparql 支持。
如果您想使用传统的关系数据库，您可以查看类似 D2RQ< /a>，或者类似 Owlgres （如果您想要推理）。
I've used sesame extensively in my projects at work. I've found it to be speedy and reliable enough for most situations I find myself in. It has definitely outperformed Jena's storage solutions on a variety of fronts. Sesame 1.x has faster query performance than the 2.x version, but the 2.x version has some nice features such as contexts and sparql support.
If you are looking to use a traditional relational database, you could look at something like D2RQ, or something like Owlgres (if you want inferencing).
一个直觉是，如果您有大量实体，元组存储可以让您免去在表之间切换时索引经常被内存耗尽的麻烦，而始终将元组索引的前几级存储在 RAM 中。
One intuition is that if you have a very large number of entities, tuple stores can save yourself the trouble of having your indexes routinely knocked out of memory as you switch between tables, and instead always have the first couple levels of the tuple index in RAM.
网络上有大量关于各种三重存储的可扩展性报告和基准测试。
这是一份很好的可扩展性报告。
W3C 本身维护着一个 wiki，其中包含有关 Large Triplestores 和 基准。
点击这 3 个链接并花点时间阅读。 这是非常有用的。 :)
There are plenny scalabity reports and benchmarks on the web about various triple-stores.
Here is a fine scalability report.
W3C itself maintain a wiki with lots of information about Large Triplestores and Benchmarks.
Follow these 3 links and take a time to read it. It's very informative. :)