Database Reference
In-Depth Information
9.7 DISCUSSION AND CONCLUSIONS
For more than a quarter of a century, the relational database management systems
(RDBMS) have been the dominant model for database management. They provide
an extremely attractive interface for managing and accessing data and have proven to
be wildly successful in many financial, business, and Internet applications. However,
with the new trends of web-scale data management, they started to suffer from some
serious limitations [28]:
Database systems are difficult to scale . Most database systems have hard
limits beyond which they do not easily scale. Once users reach these scal-
ability limits, time consuming and expensive manual partitioning, data
migration, and load balancing are the only recourse.
Database systems are difficult to configure and maintain . Administrative
costs can easily account for a significant fraction of the total cost of owner-
ship of a database system. Furthermore, it is extremely difficult for untrained
professionals to get good performance out of most commercial systems.
Diversification in available systems complicates its selection . The rise
of specialized database systems for specific markets (e.g., main memory
systems for OLTP or column stores for OLAP) complicates system selec-
tion, especially for customers whose workloads do not neatly fall into one
category.
Peak provisioning leads to unnecessary costs . Web-scale workloads are
often bursty in nature, and thus, provisioning for the peak often results in
excess of resources during off-peak phases, and thus unnecessary costs.
Recently, the new wave of NoSQL systems have started to gain some mindshares
as an alternative model for database management. In principle, some of the main
advantages of NoSQL systems can be summarized as follows:
• Elastic scaling : For years, database administrators have relied on the
scale up approach rather than the scale out approach. However, with the
current increase in the transaction rates and high availability require-
ments, the economic advantages of the scaling out approach on commod-
ity hardware has become very attractive. RDBMS might not scale out
easily on commodity clusters but NoSQL systems are initially designed
with the ability to expand transparently to take advantage of the addition
of any new nodes.
Less administration : Despite the many manageability improvements intro-
duced by RDBMS vendors over the years, high-end RDBMS systems can-
not be maintained without the assistance of expensive, highly trained DBAs.
DBAs are intimately involved in the design, installation, and ongoing tun-
ing of high-end RDBMS systems. On the contrary, NoSQL databases are
generally designed from the ground up to require less management. For
example, automatic repair and the simpler data model features should lead
to lower administration and tuning requirements.
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