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A brief intro on the idea of what is Big Data and it's potential. This is primarily a basic study & I have quoted the source of infographics, stats & text at the end. If I have missed any reference due to human error & you recognize another source, please mention.
A brief intro on the idea of what is Big Data and it's potential. This is primarily a basic study & I have quoted the source of infographics, stats & text at the end. If I have missed any reference due to human error & you recognize another source, please mention.
HYBRID DATABASE SYSTEM FOR BIG DATA STORAGE AND MANAGEMENTIJCSEA Journal
Relational database systems have been the standard storage system over the last forty years. Recently,
advancements in technologies have led to an exponential increase in data volume, velocity and variety
beyond what relational databases can handle. Developers are turning to NoSQL which is a non- relational
database for data storage and management. Some core features of database system such as ACID have
been compromised in NOSQL databases. This work proposed a hybrid database system for the storage and
management of extremely voluminous data of diverse components known as big data, such that the two
models are integrated in one system to eliminate the limitations of the individual systems. The system is
implemented in MongoDB which is a NoSQL database and SQL. The results obtained, revealed that having
these two databases in one system can enhance storage and management of big data bridging the gap
between relational and NoSQL storage approach.
HYBRID DATABASE SYSTEM FOR BIG DATA STORAGE AND MANAGEMENTIJCSEA Journal
Relational database systems have been the standard storage system over the last forty years. Recently, advancements in technologies have led to an exponential increase in data volume, velocity and variety beyond what relational databases can handle. Developers are turning to NoSQL which is a non- relational database for data storage and management. Some core features of database system such as ACID have been compromised in NOSQL databases. This work proposed a hybrid database system for the storage and management of extremely voluminous data of diverse components known as big data, such that the two models are integrated in one system to eliminate the limitations of the individual systems. The system is
implemented in MongoDB which is a NoSQL database and SQL. The results obtained, revealed that having these two databases in one system can enhance storage and management of big data bridging the gap between relational and NoSQL storage approach.
Infrastructure Considerations for Analytical WorkloadsCognizant
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HYBRID DATABASE SYSTEM FOR BIG DATA STORAGE AND MANAGEMENTIJCSEA Journal
Relational database systems have been the standard storage system over the last forty years. Recently,
advancements in technologies have led to an exponential increase in data volume, velocity and variety
beyond what relational databases can handle. Developers are turning to NoSQL which is a non- relational
database for data storage and management. Some core features of database system such as ACID have
been compromised in NOSQL databases. This work proposed a hybrid database system for the storage and
management of extremely voluminous data of diverse components known as big data, such that the two
models are integrated in one system to eliminate the limitations of the individual systems. The system is
implemented in MongoDB which is a NoSQL database and SQL. The results obtained, revealed that having
these two databases in one system can enhance storage and management of big data bridging the gap
between relational and NoSQL storage approach.
HYBRID DATABASE SYSTEM FOR BIG DATA STORAGE AND MANAGEMENTIJCSEA Journal
Relational database systems have been the standard storage system over the last forty years. Recently, advancements in technologies have led to an exponential increase in data volume, velocity and variety beyond what relational databases can handle. Developers are turning to NoSQL which is a non- relational database for data storage and management. Some core features of database system such as ACID have been compromised in NOSQL databases. This work proposed a hybrid database system for the storage and management of extremely voluminous data of diverse components known as big data, such that the two models are integrated in one system to eliminate the limitations of the individual systems. The system is
implemented in MongoDB which is a NoSQL database and SQL. The results obtained, revealed that having these two databases in one system can enhance storage and management of big data bridging the gap between relational and NoSQL storage approach.
Infrastructure Considerations for Analytical WorkloadsCognizant
Using Apache Hadoop clusters and Mahout for analyzing big data workloads yields extraordinary performance; we offer a detailed comparison of running Hadoop in a physical vs. virtual infrastructure environment.
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2. ABSTRACT:
• Our vision is that hyper databases become available that extend and evolve from
database technology. Hyper databases move up to a higher level, closer to the
applications. A hyperdata base manages distributed objects and software
components as well as workflows, in analogy to a database system that manages
data and transactions. In short, hyper databases will provide "higher order data
independence", e.g., immunity of applications against changes in the
implementation of components and workload transparency. Such an evolution of
database technology should keep its pivotal role as infrastructure for application
development for data-intensive, central and distributed application. The
hyperdata base concept abstracts from the host of current infrastructures and
middleware technology.
3. TRADITIONAL FILE BASE SYSTEM:
• A file-based data management system (also called a file system) is a type of software
that allows users to access and organize small groups of data. It is usually integrated
into a computer's operating system and is responsible for storing and retrieving files from
a storage medium, such as a hard disk or flash drive.
6. WHAT IS THE HYPERDATA BASE CONCEPT?
• A Hyperdata base (HDB) is a database over databases. A HDB administers
objects that are composed of objects and transactions that are composed of
transactions. In a more general setting we say that a HDB administers
distributed components in a networked environment and provides a kind of
higher order “data independence”. Data independence was a major
breakthrough when relational databases were propagated. Now we must
strive for immunity of application programs not only against changes in
storage and access structure but also - and this is the point here - against
changes in location, implementation, and potential replication of complete
software components and their services.
7. NEED OF HYPERDATA BASE:
• When modern database systems have been introduced twenty years ago they
have been considered as infrastructure and main platform for application
development of data-intensive applications. Data independence was found to a
breakthrough in that programmers were freed from dealing with low level details
of accessing (shared) data with respect to both performance and correct
concurrency. In the meantime the hardware and software technology has
changed dramatically. Consequently, the role of databases and database
technology in today's environment must be revisited and newly determined.
8. DIFFERENCE B/W DB AND HDB?
• A database is a collection of structured data that is stored and organized in a way that allows for easy retrieval
and manipulation. A hyperdata base, on the other hand, is a type of database that is designed to store and
manage large amounts of complex, interconnected data.
• Structure: A traditional database has a fixed schema, which defines the structure of the data stored in the
database. A hyperdata base, on the other hand, has a flexible schema that can adapt to changing data structures
and relationships.
• Interconnectedness: A traditional database stores data in tables, with each table representing a separate entity.
A hyperdata base, on the other hand, stores data in a network of interconnected nodes, with each node
representing an entity and each edge representing a relationship between two entities.
• Scalability: A traditional database can be scaled horizontally (by adding more servers) or vertically (by adding
more resources to a single server). A hyperdata base, on the other hand, is designed to scale horizontally by
adding more servers.
9. CONTI:
• Performance: Hyperdata base can handle big data, high performance, and complex
queries more efficiently than traditional databases.
10. DATA INDEPENDENCE:
• Data independence in a hyperdata base refers to the ability of the system to
decouple the physical storage of data from the logical representation of data. This
means that the system can change the way data is stored without affecting the
way the data is accessed or used by the application.
11. DECOUPLING OF DATABASE:
• In a hyperdata base, decoupling refers to the separation of the physical storage of
data from the logical representation of data. This means that the physical storage
of data, such as the location of data on disk or the specific storage technology
used, is separate from the logical representation of data, such as the schema or
the relationships between data.
12. HOW TO ACHIEVE DATA INDEPENDENCE IN
HYPER DATABASE?
• In a hyperdata base, data independence is achieved by using a flexible schema,
which allows the system to adapt to changing data structures and relationships.
Additionally, the use of a network of interconnected nodes, rather than a fixed set
of tables, allows for more flexibility in the way data is stored and accessed.