NOSQL DATABASES MONGODB VS CASSANDRA INTRODUCTION What is

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 (Data. Base 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 � Data Stored as set of tables � Accessing possible. data from different tables at the same time is

NOSQL Carlo Strozzi presented No. SQL 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 “No. Rel” � Principle Difference Popular after San Francisco conference held 2009 Why do we need No. SQL? � In SQL , efficiency in information extraction is affected by the growth of data stored & used

CAP THEOREM Based from CAP theorem, the following guarantees can be defined: � Consistency � Availability � Partition tolerance CAP theorem derives Relational and No. SQL principles

ACID “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 What if the amount of data is large? � ACID may be hard to accomplish!

BASE PRINCIPLE & NOSQL BASE principle: � Basically Available � Soft state � Eventually consistent BASE still follows CAP theorem. � Two of the three guarantees should be selected if the system is distributed.

TYPES OF NOSQL DATABASES More than 150 different No. SQL databases � Based on same principles � Has some different characteristics. Categories: � Key-value Store � Document Store � Column-family � Graph database

KEY-VALUE STORE Data is stored as a group of key and value All keys are unique Data Access is done by relating those keys to values Hash contains all keys in order to provide information when needed

DOCUMENT STORE Databases are defined as set of Key-value stores that gets transformed into documents. Each document is identified by unique key Data access can be done using: � key � specific value

COLUMN FAMILY Similar to relational database model Structure: � Column � Super-Column � Column family Structure of database is defined by super-columns and column families. Data access is accomplished by specifying column family, key and column in order to get value, using following structure: <column. Family>. <key>. <column> = <value>

GRAPH DATABASE Those databases are used when data can be represented as graph, for example, social networks.

MONGODB “Mongo. DB is an open source No. SQL database developed in C++” (Abramova & Bernardino, 2013 -07). Mongo. DB is a document store database � Documents structure are gathered into groups according to their CAP theorem � Consistency � Partition tolerance

MONGODB (CONT. ) 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 Characteristics � Durability � Concurrency

MONGODB CHARACTERISTICS Durability � Durability of data is accomplished by the creation of replicas. � Master-Slave technique Master: read & write Slave: read Slave with recent data becomes Master if the Master goes down � Replicas are asynchronous Concurrency � Locks

CASSANDRA “Cassandra is a No. SQL database developed by Apache Software Foundation; written in Java” (Abramova & Bernardino, 2013 -07) Similar to the usual relational model � Difference is that stored data can be: semi structured unstructured. CAP theorem Partition tolerance � High Availability � Designed to save large amount of data and deal with huge volumes in an efficient way.

CASSANDRA (CONT. ) Peer-to-peer architecture (NO MASTER) High availability High scalability Replicates data over multiple nodes in a cluster. 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 Fail nodes are replaced with no downtime, and they are detected using “gossip” protocols

CASSANDRA (CONT. ) Replication Strategy: � Simple: single data center � Network Topology: multiple data centers Cassandra Characteristics: � Durability: Two replication types: Synchronous Asynchronous All writes & redundancies are known using a commit log. � Indexing: “Each node maintains the indexes of the table it manages” Data is manipulated using CQL

YCSB “The YCSB – Yahoo! Cloud Serving Benchmark is one of the most used benchmarks to test No. SQL databases” (Abramova & Bernardino, 2013 -07). YCSB has a client that consists of two parts: � Workload generator � Set of workloads. Workloads are combinations of: read � Write � update operations are done on randomly chosen records. �

WORKLOAD A: 50%READS & 50% UPDATES Abramova, V. , & Bernardino, J. (2013 -07). No. SQL Databases: Mongo. DB vs Cassandra. 19

WORKLOAD B: 95%READS & 5%UPDATES Abramova, V. , & Bernardino, J. (2013 -07). No. SQL Databases: Mongo. DB vs Cassandra. 20

WORKLOAD C: 100% READS Abramova, V. , & Bernardino, J. (2013 -07). No. SQL Databases: Mongo. DB vs Cassandra. 20

WORKLOAD F: READ-MODIFY-WRITE Abramova, V. , & Bernardino, J. (2013 -07). No. SQL Databases: Mongo. DB vs Cassandra. 20

WORKLOAD G: 5% READS 95% UPDATES Abramova, V. , & Bernardino, J. (2013 -07). No. SQL Databases: Mongo. DB vs Cassandra. 20

WORKLOAD H: 100% UPDATES Abramova, V. , & Bernardino, J. (2013 -07). No. SQL Databases: Mongo. DB vs Cassandra. 21