Cloud Database Systems: NoSQL, NewSQL, Hybrid:

Limitations Of Traditional Database Architecture

The two specific Areas where the traditional database architecture is particularly limiting is IO and Transaction management.

Let's start with IO. Bottom Line, there is simply too much of hit! The implicit disk synchronization requirements create bottlenecks. Given the constraints under which the original database architects worked, it was only natural for them to focus on maintaining strict data consistency through many of the locking and latching techniques. Despite recent advances in IO, these patterns simply no longer scale to meet today's demand patterns.

The limitation is transaction management. From the below data (Figure 1) it is clear that only 12% of the time goes for processing the data request. The remaining time is for managing the buffer, locks and the latches.

The information size has expanded enormously to the scope of petabytes—one petabyte = 1,024 terabytes. RDBMS thinks that it’s testing to handle such enormous information volumes. To address this, RDBMS included more Central Processing Unit (or CPUs) or more memory to the database administration framework to scale up vertically. Most of the information arrives in a semi-organized or unstructured configuration from online networking, sound, video, messages, and messages. Be that as it may, the second issue identified by unstructured information is outside the domain of RDBMS because social databases can't sort unstructured information. They're outlined and organized to oblige organized information, for example, weblog sensor and budgetary information. Additionally, “huge information” is created at high speed. RDBMS needs in high speed since it's intended for relentless information maintenance as opposed to quick development. Regardless of the fact that RDBMS is utilized to handle and store “enormous information,” it will end up being exceptionally costly. Subsequently, the failure of social databases to handle “huge information” prompted the development of innovations.

Figure 1.

Percentage of computer cycles based on 3.5M samples

Cloud Database Management Architecture

Five layered architecture for cloud database management is shown in Figure 2. The Five Layers are as follows:

• 1.

  External Layer

• 2.

  Conceptual Middleware Layer

• 3.

  Conceptual Layer

• 4.

  Physical Middleware Layer

• 5.

  Physical Layer

Figure 2.

CDBMS