Data Received from
659MB / min
1,484MB / min
Datastore CPU Time
20 CPU-mins /
50 CPU-mins /
*Stored data is a constant metric. It does not replenish at midnight.
The datastore metrics are pretty impressive. It's hard to think of any other application
where my maximum data storage was “unlimited.” You do pay for space, but the idea
that you can't run out of it is pretty fascinating. Here are some descriptions that
better describe what the datastore metrics are and how they are measured.
Datastore API Calls : Basically, the total number of CRUD
operations on the datastore. Every time your application creates,
retrieves, updates, or deletes an entity from the datastore, this
metric increases. Queries also count toward your datastore API
Stored Data : As we mentioned above in Table 2-3's footnote, this is
not a rolling metric. Data storage is constant and does not
replenish day to day, and in the datastore, it's a bit complicated to
accurately estimate. There's a certain amount of overhead attached
to storing an entity in the datastore. To do this, the following types
of metadata are required:
1. Each entity requires a key. This includes the kind (type), the ID
or key name, and the key of the entity's parent entity.
2. The datastore is schemaless. So, the name and value of each
property must be stored in the datastore. This is very different
from a relational database where you are storing only the data
values. For each entity's attributes you have to store the name
and the value in the datastore.