Google Cloud Bigtable和Google Cloud datastore / App Engine数据存储有什么不同,主要的实际优势/劣势是什么?AFAIK云数据存储构建在Bigtable之上。
发布于 2015-05-07 04:30:57
Bigtable和Datastore是非常不同的。是的,数据存储是建立在Bigtable之上的,但这并不意味着它就像它一样。这有点像是说汽车是建立在轮子上的,所以汽车和轮子没有太大的区别。
Bigtable和Datastore在如何更改数据方面提供了非常不同的数据模型和非常不同的语义。
主要区别在于,数据存储在称为实体组的数据子集上提供类似SQL数据库的ACID事务(尽管查询语言GQL比SQL有更多限制)。Bigtable是严格意义上的NoSQL,它的保证要弱得多。
发布于 2019-03-05 04:08:57
我将尝试总结上面的所有答案以及课程A Google Cloud Platform Big Data and Machine Learning Fundamentals中给出的内容
+---------------------+------------------------------------------------------------------+------------------------------------------+--+
| Category | BigTable | Datastore | |
+---------------------+------------------------------------------------------------------+------------------------------------------+--+
| Technology | Based on HBase(uses HBase API) | Uses BigTable itself | |
| ---------------- | | | |
| Access Mataphor | Key/Value (column-families) like Hbase | Persistent hashmap | |
| ---------------- | | | |
| Read | Scan Rows | Filter Objects on property | |
| ---------------- | | | |
| Write | Put Row | Put Object | |
| ---------------- | | | |
| Update Granularity | can't update row ( you should write a new row, can't update one) | can update attribute | |
| ---------------- | | | |
| Capacity | Petabytes | Terbytes | |
| ---------------- | | | |
| Index | Index key only (you should properly design the key) | You can index any property of the object | |
| Usage and use cases | High throughput, scalable flatten data | Structured data for Google App Engine | |
+---------------------+------------------------------------------------------------------+------------------------------------------+--+
也检查一下这张图片:
https://stackoverflow.com/questions/30085326
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