An Overview of the NoSQL World - Large Scale and Big Data: Processing and Management - page 305

In principle, choosing the adequate NoSQL system (from the very wide available
spectrum of choices) with design decisions that best fit with the requirements of a
software application is not a trivial task and requires careful consideration. Table 9.1
provides an overview of different design decision for sample NoSQL systems.
In practice, transactional data management applications (e.g., banking, stock trad-
ing, supply chain management) that rely on the ACID guarantees that databases pro-
vide, tend to be fairly write-intensive or require microsecond precision and are less
obvious candidates for the cloud environment until the cost and latency of wide-area
data transfer decreases. Cooper et al. [26] discussed the tradeoffs facing cloud data
management systems as follows:

• Read performance vs. write performance : Log-structured systems that only

store update deltas can be very inefficient for reads if the data is modified
over time. On the other hand, writing the complete record to the log on
each update avoids the cost of reconstruction at read time but there is a cor-
respondingly higher cost on update. Unless all data fits in memory, random
I/O to the disk is needed to serve reads (e.g., as opposed to scans). However,
for write operations, much higher throughput can be achieved by appending
all updates to a sequential disk-based log.

• Latency vs. durability : Writes may be synched to disk before the system

returns success to the user or they may be stored in memory at write time
and synched later. The advantages of the latter approach are that avoid-
ing disk access greatly improves write latency, and potentially improves

TABLE 9.1
Design Decisions of Various Web-Scale Data Management Systems
System

Data Model Query Interface Consistency CAP Options License

Bigtable Column Families Low-Level API Strict CP Internal at Google

Google
AppEng

Column Families Python

API-GQL

Strict CP Commercial

PNUTS Key-Value Store Low-Level API Multiple AP Internal at Yahoo

Dynamo Key-Value Store Low-Level API Eventual AP Internal at

Amazon

S3 Large Objects

Store

Low-Level API Eventual AP Commercial

SimpleDB Key-Value Store Low-Level API Multiple AP Commercial

RDS Relational Store SQL Strict CA Commercial

SQL Azure Relational Store SQL Strict CA Commercial

Cassandra Column Families Low-Level API Tunable AP Open source—

Apache

Hypertable Multidimensional

Table

Low-Level API,
HQL

Eventual AP Open source—

GNU

CouchDB Document-

Oriented Store

Low-Level API Eventual AP Open source—

Apache