1. WOLAITA SODO UNIVERSITY SHOOL OF INFORMATICS
DEPARTMENT; INFORMATION TECHNOLOGY
PROGRM; POST GRADUATE
SESSION : REGULAR
PRESENTATION TITEL:CALLABLE AND REPLICATED SHARED
OBJECTS OVER NOSQL
GROUP MEMBERS ID-NO
1, Abebe Tora PGR/82835/15
2, Wondimagegn desta PGR/82842/15
3, Gizework Alemayehu PGR/62915/14
Submitted to - Desta Dana (Asst. Prof. in IT)
Sub. Date: - June 14/2023
2. Terminology
• Node: Networked computer that offers some kind of
service, local storage and access to a larger distributed
system or file store.
• Clusters: Set of nodes.
• Sharding (or horizontal partitioning): Partitioning the
database on the value of some field.
• Replication: Portions of data are written to multiple
nodes in case one of them fails (ensuring availability).
• ACID: Atomicity, Consistency, Isolation, Durability. Is a
set of properties of database transactions intended to
guarantee validity even in the event of errors, power
failures, etc.
• BASE: Basically available (no 24/7 availability), soft-
state (database may be inconsistent) and eventually
consistent (eventually, it will be consistent).
3. Abstract
• I n a Cloud environment, the ability to share and
persist objects simplifies the design of
applications.
• Storing objects in a NoSQL database ensures
their availability and provides scalability to
applications.
• When Object-NoSQL Mapping is performed at
the client side, objects that are accessed by
several clients are repeatedly converted between
their in-memory and serialized representations.
4. Introduction
• NoSQL databases have existed since the 1960s, but have
been recently gaining traction with popular options such as
MongoDB, CouchDB, …..etc
• NoSQL stands for:
o No Relational
o No RDBMS
o Not Only SQL
• NoSQL is an umbrella term for all databases and data stores
that don’t follow the RDBMS principles
o A class of products
o A collection of several (related) concepts about data storage and
manipulation
o Often related to large data sets
5. Continu..
• NoSQL databases are currently a hot topic in
some parts of computing, with over a hundred.
• NoSQL is also type of distributed database,
which means that information is copied and
stored on various servers, which can be
remote or local . This ensures availability and
reliability of data
6.
7. NoSQL Database Types
Discussing NoSQL databases is complicated
because there are a variety of types:
• Graph stores are used to store information about networks of
data, such as social connections. Graph stores include Neo4J
and triple stores like Fuseki.
• Document databases pair each key with a complex data
structure known as a document.
• Key-value stores are the simplest NoSQL databases. Every
single item in the database is stored as an attribute name (or
'key'), together with its value. Examples of key-value stores are
Riak and Berkeley DB.
• Wide-column stores such as Cassandra and HBase are
optimized for queries over large datasets, and store columns of
data together, instead of rows.
8. Advantage of noSQL
• Elastic scalability: These databases are designed for
use with low-cost commodity hardware.
• Big Data Applications: Massive volumes of data are
easily handled by NoSQL databases.
• Auto-sharding: Relational Databases scale vertically,
which means you often have a lot of databases
spread across multiple servers because of the disk
space they need to work.
9. • Replication: Most NoSQL databases also
support automatic database replication to
maintain availability in the event of outages or
planned maintenance events.
• Integrated caching: Many NoSQL technologies
have excellent integrated caching capabilities,
keeping frequently-used data in system
memory as much as possible and removing
the need for a separate caching layer.
10. Disadvantages of NoSQL
• No standardization rules
• Limited query capabilities
• RDBMS databases and tools are comparatively mature
• It does not offer any traditional database capabilities,
like consistency when multiple transactions are
performed simultaneously.
• When the volume of data increases it is difficult to
maintain unique values as keys become difficult
• Doesn’t work as well with relational data
• The learning curve is stiff for new developers
• Open source options so not so popular for enterprises.
