An Overview of the NoSQL World - Large Scale and Big Data: Processing and Management - page 300

not have an OR operator. However, it does have an IN operator that provides a lim-
ited form of OR . The optional ORDER BY clause indicates that results should be
returned are sorted by the given properties in either ascending (ASC) or descending
(DESC) order. An optional LIMIT clause causes the query to stop returning results
after the first count entities. The LIMIT can also include an offset to skip the speci-
fied number of results to find the first result to be returned. An optional OFFSET
clause can specify an offset if the no LIMIT clause is present. Chohan et al. [23]
have presented AppScale as an open-source extension to the Google AppEngine that
facilitates distributed execution of its applications over virtualized cluster resources,
including Infrastructure-as-a-Service (IaaS) cloud systems such as Amazon EC2 and
Eucalyptus.* They have used AppScale to empirically evaluate and compare how
well different NoSQL systems (e.g., Cassandra, HBase, Hypertable, MemcacheDB,
MongoDB, Voldemort) map to the GAE Datastore API [16].
Google Cloud SQL † is another Google service that provide the capabilities and
functionality of MySQL database servers, which are hosted in Google's cloud.
Although there is tight integration of the services with the Google App Engine , it
allows the software applications to easily move their data in and out of Google's
cloud without any obstacles.
9.4.2 a mazon : s3/s imPle Db/a mazon rDs
Amazon Simple Storage Service (S3) is an online public storage web service offered
by Amazon Web Services. Conceptually, S3 is an infinite store for objects of variable
sizes. An object is simply a byte container, which is identified by a URI. Clients can
read and update S3 objects remotely using a simple web services (SOAP or REST-
based) interface. For example, get ( uri ) returns an object and put ( uri, bytestream )
writes a new version of the object. In principle, S3 can be considered as an online
backup solution or for archiving large objects, which are not frequently updated.
Amazon has not published details on the implementation of S3. However,
Brantner et al. [14] have presented initial efforts of building web-based database
applications on top of S3. They described various protocols for storing, reading,
and updating objects and indexes using S3. For example, the record manager com-
ponent is designed to manage records where each record is composed of a key and
payload data. Both key and payload are bytestreams of arbitrary length where the
only constraint is that the size of the whole record must be smaller than the page
size. Physically, each record is stored in exactly one page, which in turn is stored
as a single object in S3. Logically, each record is part of a collection (e.g., a table).
The record manager provides functions to create new objects, read objects, update
objects, and scan collections. The page manager component implements a buffer
pool for S3 pages. It supports reading pages from S3, pinning the pages in the buf-
fer pool, updating the pages in the buffer pool, and marking the pages as updated.
All these functionalities are implemented in a straightforward way just as in any
standard database system. Furthermore, the page manager implements the commit
* http://www.eucalyptus.com/.
† https://developers.google.com/cloud-sql/.