2. Table of
content
• What is No SQL ?
• No SQL types
• What are NoSQL features ?
• ACID and CAP Theorems
• What is mongo DB ?
• Fast install mongo DB using docker container
• Create database in mongo db
• Create mongo db collections
• Mongo db CRUD operations
3. What is
NoSQL ?
• When people use the term “NoSQL
database”, they typically use it to refer to any
non-relational database. Some say the term
“NoSQL” stands for “non SQL” while others say
it stands for “not only SQL.” Either way, most
agree that NoSQL databases are databases
that store data in a format other than
relational tables
• The data structures used by NoSQL
databases
• Differ from those used in relational
databases
4. No SQL Types
Type Example
Key-value Store Redis
Wide column Store Cassandra , H.Base
Document Store Mongodb , Couchdb
Graph Store Neo4j,Infinite Graph
5. Key-Value
Store
Key Value Store NoSQL Database it is most
simplest NoSQL databases
Every single item in the database is stored as
an attribute key together with its value witch
key is unique . Key-value databases are highly
partitionable and allow horizontal scaling.
Key-Value Store offer Randomly access to data
by key like hash-table or dictionary data-
structures witch time complexly of reading is
o(1).
Use Case : Session store such as user
information
6. column Store
The column store databases are used to optimized
queries over large datasets and store columns of
data together instead of rows.
Columns store databases use a concept called a key
space. A key space is kind of like a schema in the
relational model. The key space contains all the
column families (kind of like tables in the relational
model), which contain rows, which contain
columns.
Use case : Data-intensive applications
7. Document
Store
A document database is a type of nonrelational
database that is designed to store and query data as
JSON-like documents. Document databases make it
easier for developers to store and query data in a
database by using the same document-model format
they use in their application code.
Document database offer flexibility to update entities
So if the data model needs to change, only the
affected documents need to be updated. No schema
update is required and no database downtime is
necessary to make the changes.
Use case :
Content management system such as blogs and video
8. Graph Store
• a graph database is a database designed to treat the
relationships between data as equally
• important to the data itself. It is intended to hold data
without constricting it to a pre-defined model.
• Instead, the data is stored like we first draw it out –
showing how each individual entity connects with or is
related
• to others.
• Also Graph databases are a special kind
of database storing complex data structures that would
be infeasible to store in a traditional
• relational database. They're most notably used for social
networks, as they're much more performant for certain
queries.
• Use Case : Social media connections
10. ACID and CAP
Theorems
ACID theorem :
(atomicity, consistency, isolation, durability) is a set of properties
of database transactions intended to guarantee validity even in the
event of errors)
Atomicity : A transaction is an atomic unit; hence, all the instructions
within a transaction will successfully execute, or none of them
will execute. The following transaction transfers 20 dollars from Alice’s
bank account to Bob’s bank account. If any of the instructions
fail, the entire transaction should abort and rollback.
Consistency : A database is initially in a consistent state, and it should
remain consistent after every transaction. Suppose that the
transaction in the previous example fails after Write(A_b) and the
transaction is not rolled back; then, the database will be inconsistent as
the sum of
Alice and Bob’s money, after the transaction, will not be equal to the
amount of money they had before the transaction.
Isolation : refers to the requirement that other operations cannot access
or see the data in an intermediate state during a transaction.
Durability : refers to the guarantee that once the user has been notified
of success , the transaction will persist and not be undone.
11. CAP Theorem
The CAP theorem (also called Brewer’s theorem after
computer scientist Eric Brewer, states that it is
impossible for a distributed data store to
simultaneously provide more than two out of the
following three guarantees) also that a distributed
database system can only guarantee two out of these
three characteristics: Consistency, Availability, and
Partition Tolerance.
12. Consistency
A system is said to be consistent if all nodes see the
same data at the same time.
Simply, if we perform a read operation on a
consistent system, it should return the value of the
most recent write operation. This means that, the
read should cause all nodes to return the same
data, i.e., the value of the most recent write.
13. Consistency
between ACID
and CAP
ACID consistency is all about
database rules. If a schema declares
that a value must be unique, then a
consistent system will enforce
uniqueness of that value across all
operations. If a foreign key implies
deleting one row will delete related
rows, then a consistent system will
ensure the state can’t contain related
rows once the base row is deleted.
CAP consistency promises that every
replica of the same logical value,
spread across nodes in a distributed
system, has the same exact value at
all times. Note that this is a logical
guarantee, rather than a physical one.
Due to the speed of light, it may take
some non-zero time to replicate
values across a cluster. The cluster
can still present a logical view by
preventing clients from viewing
different values at different nodes.
14. Availability
• Availability in a distributed system ensures
that the system remains operational 100% of
the time. Every request gets a (non-error)
response regardless of the individual state of a
node.
• Note: this does not guarantee that the
response contains the most recent write.
15. Partition Tolerance
This condition states that the system continues to run, despite the
number of messages being delayed by the network between nodes. A
system that is partition-tolerant can sustain any amount of network
failure
that doesn’t result in a failure of the entire network. Data records are
sufficiently replicated across combinations of nodes and networks to
keep the
system up through intermittent outages. When dealing with modern
distributed systems, Partition Tolerance is not an option. It’s a necessity.
Hence, we have to trade between Consistency and Availability.
16. What is mongo DB
?
• MongoDB is a free and open-
source cross-platform document
oriented database
• MongoDB is a document database
with the scalability and flexibility that
you want with the querying and
indexing that you need.
• Mongo uses JSON-like documents
with schemas .
• In mongo you can CREATE-UPDAT-
READ-DELETE data
17. MongoDB in
CAP ?
• Mongo is Constance and partition tolerated but not Highly
available
• MongoDB is a single leader based system that can have
multiple replicas. These replicas update themselves
asynchronously from Leader’s.
• Each node maintains the heartbeat of every other node to
keep track if other replicas or leader is alive or dead.
• If the leader/primary node goes down, replicas can identify
and elect a new leader based on priority, if they can form
the majority.
• Mongo db not available because If a leader disconnects
from the cluster, it takes a few seconds to elect a new
leader. So, making it unavailable for writes and reads.
18. Fast install mongo DB using docker container
• For fast installation mongoDB we will
use docker container but do not do this
way in the production.
• To run mongoDB inside docker use the
following command
• docker run -d -p 27017-27019:27017-
27019 --name mongodb mongo
19. Create
database in
mongo db
• To Create a new database in mongodb we will
use mongo CLI inside our mogodb docker
container
• 1- open bash in the docker container by using
the following command
• docker exec –it {container name or id} bash
• 2- after open mongodb container bash type
“mongo” to start connect to your mongo cluster
• 3- To create a new mongodb just type “use
{your database name}”
20. Mongodb
CRUD
• To create a new mongo collection use the following command
db.createCollection(collection Name)
• To insert a new document in a collection use the following command
db.{collection Name}.insert({JSON})
Example : db.users.insert({name : “mohammed ragab”,title : “Senior software
engineer”,teams : [“aptar”]});
• To read data from collection use the following command
db.{collection Name}.find();
Example : db.users.find() this command will return all documents
db.users.findOne() this command will return the first document
db.users.find({name : “mohammed ragab”}) this will return all documents that have
name equal “mohammed ragab”
• To Update document in a collection use the following command
db.users.update({‘condtion field ‘ : ‘value’ }, {new JSON}})
Example :
db.users.update({'name' : 'mohammed ragab'},{'name' : 'mohammed ragab ali’})
• To Delete a document in collection use the following command
• db.users.remove({'name' : 'mohammed ragab ali'})
21. Thank You !!
I hope the session was useful
Mohammed Ragab
