NoSQL Databases: MongoDB vs Cassandra

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NOSQL DATABASES:
MONGODB VS CASSANDRA
INTRODUCTION

What is a Database?
 “… a repository with organized and structured data, … “
(Abramova & Bernardino, 2013-07)


Data can be accessed using DBMS (DataBase
Management System)
What is DBMS?
 “ DBMS can be defined as a collection of mechanisms
that enables storage, edit and extraction of data” (Abramova
& Bernardino, 2013-07)
SQL

SQL: Structured Query Language

Became standard for:
Data interaction
 Data manipulation
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Data Stored as set of tables

Accessing data from different tables at the same time
is possible.
NOSQL


Carlo Strozzi presented NoSQL in 1980, back then, it
refers to an open source database that didn’t use SQL
interface.
Carlo Strozzi preferred to call it “noseequel” or
“NoRel”
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Principle Difference

Popular after San Francisco conference held 2009

Why do we need NoSQL?

In SQL ,efficiency in information extraction is affected by
the growth of data stored & used
CAP THEOREM
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Based from CAP theorem, the following
guarantees can be defined:
Consistency
 Availability
 Partition tolerance
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CAP theorem derives Relational and NoSQL
principles
ACID
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“ACID is a principle based on CAP theorem and
used as set of rules for relational database
transactions.“ (Abramova & Bernardino, 2013-07)
ACID guarantees:
Atomic
 Consistent
 Isolated
 Durable
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What if the amount of data is large?
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ACID may be hard to accomplish!
BASE PRINCIPLE & NOSQL
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BASE principle:
Basically Available
 Soft state
 Eventually consistent
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BASE still follows CAP theorem.

Two of the three guarantees should be selected if the
system is distributed.
TYPES OF NOSQL DATABASES
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More than 150 different NoSQL databases
Based on same principles
 Has some different characteristics.


Categories:
Key-value Store
 Document Store
 Column-family
 Graph database
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KEY-VALUE STORE
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Data is stored as a group of key and value
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All keys are unique
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Data Access is done by relating those keys to
values
Hash contains all keys in order to provide
information when needed
DOCUMENT STORE
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Databases are defined as set of Key-value stores
that gets transformed into documents.
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Each document is identified by unique key
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Data access can be done using:
key
 specific value
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COLUMN FAMILY
Similar to relational database model
 Structure:
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Column
 Super-Column
 Column family

Structure of database is defined by supercolumns and column families.
 Data access is accomplished by specifying column
family, key and column in order to get value,
using following structure:
 <columnFamily>.<key>.<column> = <value>
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GRAPH DATABASE
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Those databases are used when data can be
represented as graph, for example, social
networks.
MONGODB


“MongoDB is an open source NoSQL database
developed in C++” (Abramova & Bernardino, 2013-07).
MongoDB is a document store database


Documents are gathered into groups according to
their structure
CAP theorem
Consistency
 Partition tolerance
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MONGODB (CONT.)
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Description
Data is sent to disc every 60 seconds.
 Everything is flushed to disc once new files are
created
 Each document is identified by “id” field
 An index for the “id” field is created
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Characteristics
Durability
 Concurrency
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MONGODB CHARACTERISTICS
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Durability
Durability of data is accomplished by the creation of
replicas.
 Master-Slave technique
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Master: read & write
 Slave: read
 Slave with recent data becomes Master if the Master goes
down
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Replicas are asynchronous
Concurrency
 Locks
CASSANDRA
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“Cassandra is a NoSQL database developed by Apache
Software Foundation; written in Java” (Abramova & Bernardino, 2013-07)
Similar to the usual relational model
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Difference is that stored data can be:
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semi structured
unstructured.
CAP theorem
Partition tolerance
 High Availability
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Designed to save large amount of data and deal with
huge volumes in an efficient way.
CASSANDRA (CONT.)
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Peer-to-peer architecture (NO MASTER)


High availability
High scalability
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Replicates data over multiple nodes in a cluster.
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Replication Factor: Total number of replicas.
RF(1): 1 copy of each row on 1 node
 RF(2): 2 copies of same records on 2 nodes
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Fail nodes are replaced with no downtime, and
they are detected using “gossip” protocols
CASSANDRA (CONT.)
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Replication Strategy:
Simple: single data center
 Network Topology: multiple data centers
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Cassandra Characteristics:
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Durability:
Two replication types:
 Synchronous
 Asynchronous
 All writes & redundancies are known using a commit log.
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Indexing:

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“Each node maintains the indexes of the table it manages”
Data is manipulated using CQL
YCSB

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“The YCSB – Yahoo! Cloud Serving Benchmark
is one of the most used benchmarks to test
NoSQL databases” (Abramova & Bernardino, 2013-07).
YCSB has a client that consists of two parts:
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Workload generator
Set of workloads.
Workloads are combinations of:
read
 Write
 update
operations are done on randomly chosen records.
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WORKLOAD A: 50%READS & 50% UPDATES
Abramova, V., & Bernardino, J. (2013-07). NoSQL Databases: MongoDB vs Cassandra. 19
WORKLOAD B: 95% READS & 5%UPDATES
Abramova, V., & Bernardino, J. (2013-07). NoSQL Databases: MongoDB vs Cassandra. 20
WORKLOAD C: 100% READS
Abramova, V., & Bernardino, J. (2013-07). NoSQL Databases: MongoDB vs Cassandra. 20
WORKLOAD F: READ-MODIFY-WRITE
Abramova, V., & Bernardino, J. (2013-07). NoSQL Databases: MongoDB vs Cassandra. 20
WORKLOAD G: 5% READS 95% UPDATES
Abramova, V., & Bernardino, J. (2013-07). NoSQL Databases: MongoDB vs Cassandra. 20
WORKLOAD H: 100% UPDATES
Abramova, V., & Bernardino, J. (2013-07). NoSQL Databases: MongoDB vs Cassandra. 21

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