605 3AB

Exactly from my textbook below:

Cloud Storage Device

Block storage requires data to be in a fixed format (known as a data block), which is the

smallest unit that can be stored and accessed and the storage format closest to hard-

ware. Using either the logical unit number (LUN) or virtual volume block-level storage

will typically have better performance than fi le-level storage.

Object Storage Interfaces

Various types of data can be referenced and stored as Web resources. This is referred

to as object storage, which is based on technologies that can support a range of data

and media types. Cloud Storage Device mechanisms that implement this interface can

typically be accessed via REST or Web service-based cloud services using HTTP as the

prime protocol. The Storage Networking Industry Association’s Cloud Data Management Interface (SNIA’s CDMI) supports the use of object storage interfaces.

Database Storage Interfaces

Cloud storage device mechanisms based on database storage interfaces typically sup-

port a query language in addition to basic storage operations. Storage management is

carried out using a standard API or an administrative user-interface.

This classifi cation of storage interface is divided into two main categories according to

storage structure, as follows.

Relational Data Storage

Traditionally, many on-premise IT environments store data using relational databases

or relational database management systems (RDBMSs). Relational databases (or rela-

tional storage devices) rely on tables to organize similar data into rows and columns.

Tables can have relationships with each other to give the data increased structure, to

protect data integrity, and to avoid data redundancy (which is referred to as data nor-

malization). Working with relational storage commonly involves the use of the industry

standard Structured Query Language (SQL).

A cloud storage device mechanism implemented using relational data storage could be

based on any number of commercially available database products, such as IBM DB2,

Oracle Database, Microsoft SQL Server, and MySQL.

Challenges with cloud-based relational databases commonly pertain to scaling and

performance. Scaling a relational cloud storage device vertically can be more complex

and cost-ineffective than horizontal scaling. Databases with complex relationships and/

or containing large volumes of data can be affl icted with higher processing overhead

and latency, especially when accessed remotely via cloud services.

Non-Relational Data Storage

Non-relational storage (also commonly referred to as NoSQL storage) moves away from the traditional relational database model in that it establishes a “looser” structure for stored data with less emphasis on defi ning relationships and realizing data normaliza-tion. The primary motivation for using non-relational storage is to avoid the potential complexity and processing overhead that can be imposed by relational databases. Also, non-relational storage can be more horizontally scalable than relational storage. The trade-off with non-relational storage is that the data loses much of the native form and validation due to limited or primitive schemas or data models. Furthermore, non-relational repositories don’t tend to support relational database functions, such as trans-actions or joins.Normalized data exported into a non-relational storage repository will usually become denormalized, meaning that the size of the data will typically grow. An extent of nor-malization can be preserved, but usually not for complex relationships. Cloud providers often offer non-relational storage that provides scalability and availability of stored data over multiple server environments. However, many non-relational storage mechanisms are proprietary and therefore can severely limit data portability.