Database Reference
In-Depth Information
If you want to run analytics queries over your Cloud Datastore storage, you
can export it to BigQuery. Chapter 11, “Managing Data Stored in BigQuery,”
shows one way of exporting AppEngine data automatically, whereas Chapter
12 shows another mechanism you can use if you want to transform the
data in the process. A number of BigQuery customers store their data both
in BigQuery and Datastore by writing simultaneously to both locations.
Although this seems like unnecessary duplication, it allows for both fast
point-lookups (via Datastore) and fast ad hoc queries (via BigQuery).
Cloud SQL
Google Cloud SQL is a cloud-hosted MySQL database. The query language
is MySQL, and the performance characteristics are similar to MySQL.
However, running it in Google's storage infrastructure helps it scale better
than a stock MySQL instance.
Cloud SQL is extremely helpful if you're migrating an existing application to
Google's cloud. If your application is currently using a relational database
(like MySQL or PostgreSQL), it might be difficult to switch to using a NoSQL
store like Cloud Datastore. Cloud SQL allows you to run the same SQL
queries you're used to but within Google's managed cloud.
Although it has a familiar interface, Cloud SQL has many of the scaling
limitations of MySQL, and if you have a large amount of data you might
consider using Cloud Datastore and/or BigQuery instead.
Table 2.1
has a
comparison of the features between BigQuery and Cloud SQL to help you
decide which one is better for your application.
