This document provides a summary of a presentation that benchmarked the performance of three popular NoSQL databases: Apache Cassandra, Apache HBase, and MongoDB. It describes the architectures and data models of each database. Benchmark tests were run using the Yahoo Cloud Serving Benchmark and found that Apache Cassandra consistently outperformed the other databases across different workloads in terms of load time, read and write performance, and latency. The presentation emphasizes the importance of benchmarks for evaluating NoSQL database performance and choosing the right database based on application requirements.

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Einrichtung Titel des Vortrages 1
WP-Benchmarking Top NoSQL
Databases
Apache Cassandra, Apache HBase and MongoDB
Presented By
Athiq Ahamed
Supriya

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Einrichtung Titel des Vortrages 2
Introduction
 Enormous amount of data-BigData
 Scalabilty issue in RDBMS
 Rise of NoSQL databases
 Amazon Dynamo
 Big table
 CAP Theorem
 BASE system

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Einrichtung Titel des Vortrages 3
CAP Theorem
 Consistency
 Availability
 Partition tolerance
CAP theorem states that only two of the properties can be
achieved at a time.

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Einrichtung Titel des Vortrages 4
RDBMS NoSQL
Supports powerful query
language
Supports very simple query
language
It has a fixed schema No fixed schema
Follows ACID (Atomicity,
Consistency, Isolation and
Durability)
It is only eventually consistent
Supports transactions Does not support transactions
RDBMS vs NoSQL
Content:tutorialspoint.com

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Einrichtung Titel des Vortrages 5
 Basically available: System guarantees availability, in
terms of the CAP theorem
 Soft state: State of the system may change over time,
because of eventual consistency model
 Eventual consistency: System will become consistent over
time
BASE
Content:www.edureka.in

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Einrichtung Titel des Vortrages 6
 Fast Performance is the key.
 POC processes include right benchmarks:
 Configurations
 Parameters
 Workloads
Making the right choice!
Selection of NoSQL

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Einrichtung Titel des Vortrages 7
 Yahoo Cloud Serving Benchmark (YCSB)
 Top 3 NoSQL databases-Apache Cassandra, Apache
Hbase and MongoDB.
 Amazon Web Services EC2 instances for hosting the tests
 Test performed 3 times on 3 different days
Benchmark configuration

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Einrichtung Titel des Vortrages 8
 The tests ran on large size instances (15GB RAM and 4
CPU cores)
 Instances used customized Ubuntu with Oracle Java 1.6
installed as a base.
 A customized script written to drive the benchmark
processes
Benchmark configuration

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Einrichtung Titel des Vortrages 9
 Each NoSQL system performs differently, not alike.
 Components and Internal working.
 Apache Cassandra: Columnar database model
 Apache HBase: Columnar database model
 MongoDB: Document storage database model
Understanding NoSQL Databases

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Einrichtung Titel des Vortrages 10
Apache Cassandra
 Cassandra is scalable, fault-tolerant, and consistent. All
nodes are equal.
 Its distribution design is based on Amazon’s Dynamo and
its data model on Google’s Bigtable.
 Key components: Node, Cluster, Commit log, Mem-table,
SSTable and Bloom filter
Content:http://www.tutorialspoint.com/cassandra/cassandra_architecture.htm

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Einrichtung Titel des Vortrages 11
 Ring structure, peer to peer architecture
 All nodes are equal
 This improves general database availablity
 Scaling up and scaling down is easier
 Cassandra has key-value, column oriented database
Apache Cassandra

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Einrichtung Titel des Vortrages 12
Apache Cassandra
Content:http://demoiselle.sourceforge.net/component/demoiselle-
cassandra/1.0.0/images/datamodel1.png

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Einrichtung Titel des Vortrages 13
 Cassandra has an internal keyspace called system, stores
metadata about the cluster.
 Metadata:
 The node‘s token
 The cluster name
 Keyspace n schema definitions (dynamic loading)
 Whether or not the node is bootstrapped
Apache Cassandra
Content:https://www.edureka.co/blog/category/apache-cassandra/

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Einrichtung Titel des Vortrages 14
 Commit log: Crash recovery mechanism. Every write
operation is written to commit log
 Mem-Table: A memory resident data structure.
 SSTable: It is a disk file to which the data is flushed from
the mem-table
Apache Cassandra

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Einrichtung Titel des Vortrages 15
 Bloom filters are used as a performance booster
 Bloom filter are very fast, quick algorithms for testing a
member in the set.
 Bloom filters serves as a special kind of cache – quick
lookups/search as they reside in memory
Apache Cassandra

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Einrichtung Titel des Vortrages 16
 Gossip protocol: Communiction between nodes, co-
ordination and failure check
 Anti-Entropy protocol: Replica sync mechanism enusing
data on different nodes are updated (Merkle trees)
 Snitches ensures host proximity
Apache Cassandra

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Einrichtung Titel des Vortrages 17
Apache Cassandra- Read/Write operation

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Einrichtung Titel des Vortrages 18
 Sparse, distributed, sorted map and multidimensional and
consistent.
 Hbase is a Key/value store
 Consists Row key, Column family, columns and timestamp.
Apache HBase

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Einrichtung Titel des Vortrages 19
Apache HBase
Content:http://zhangjunhd.github.io/assets/2013-02-25-apache-hbase/rowkey-

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Einrichtung Titel des Vortrages 20
 Region: Contiguous rows form a region
 Region server(RS): Serves one or more regions.
 Master server: Daemon responsible for managing Hbase
cluster
 HDFS: Distributed, open source file system containing
HBase‘s data
 Zookeeper: Distributed, open source co-ordinated service
for co-ordination of master and region servers.
Apache HBase Components
Content: https://www.mapr.com/blog/in-depth-look-hbase-architecture

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Einrichtung Titel des Vortrages 21
Apache Hbase Architecture

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 Client obtains meta table RS from Zookeeper
 Client gets RS which holds the corresponding rowkey
 Client receives the row from the respective Region server
 Client caches this information along with the location of
meta table server.
First Read/Write to HBase

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Einrichtung Titel des Vortrages 23
 WAL: Write Ahead Log is a file on the distributed file
system. It is used to store new data
 Block Cache: It is the read cache. It stores frequently
read data in memory
 Mem Store: Write cache that stores new data which is not
written to disk yet.
 Hfiles stores the rows as sorted key values on disk
HBase RS Components

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Einrichtung Titel des Vortrages 24
 Client writes the data to the WAL file stored on disk
 WAL is used to recover not yet persisted data in case a
server crashes.
 Once data is written to WAL, it is placed in Mem Store
Hbase Write steps (1)

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Einrichtung Titel des Vortrages 25
 All write/read are to/from the primary node.
 HDFS replicates WAL and Hfile blocks. Replication
happens automatically.
 When data is written in HDFS, one copy is written locally
and then it is replicated to a secondary node and later to
tertiary node.
HDFS Write steps (2)

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Einrichtung Titel des Vortrages 26
 Cassandra usecase: Availability and Partition tolerant
requirements.
Consistency is tunable by setting it high in the option
 Hbase usecase: Consistency and Scalability. However, at
less number of nodes/threads, availability is achieved high
Cassandra and Hbase

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Einrichtung Titel des Vortrages 27
 Document-oriented database
 High performance and automatic scaling
 High consistency and partition tolerant
 Replication and failover for high availability
 Low latency
 Flexible indexing
MongoDB

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Einrichtung Titel des Vortrages 28
 Document is the basic unit for MongoDB(row)
 Collection is similar to a table
 A single instance has multiple independent databases
 Every document has a special key, “_id”
 Powerful JavaScript shell for administration
 Configdb contains metadata of clusters
MongoDB Concepts

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Einrichtung Titel des Vortrages 29
MongoDB Simple Architecture

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 A mongo receives queries from applications
 Uses metadata from config server for the data
 Mangos directs write operations to a particular shard
 Mongos uses the cluster metadata from the config
database
Read/Write MongoDB

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Einrichtung Titel des Vortrages 31
 Scalability
 Availability
 Partition Tolerant
 Consistency
MOST IMPORTANT PERFORMANCE
Yahoo Cloud Serving Benchmark (YCSB)
Recap Importance of Benchmark and Factors

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Einrichtung Titel des Vortrages 32
Results: Load Process

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Einrichtung Titel des Vortrages 33
Results: Read/Write Mix Workload

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Results: Read/Scan Mix Workload

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Results: Read Latency across all workloads

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Results: Insert Latency across all workloads

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Einrichtung Titel des Vortrages 37
Lets MIGRATE from traditional data base !!!!
Live Demo

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Einrichtung Titel des Vortrages 38
 Identify data model for the application
 Corresponding data sets have to be known
 Whether the application requires replication
 Identify the performance requirements
 Prototype the application
 Test the performance of the prototype
Discussion

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Einrichtung Titel des Vortrages 39
Conclusion
 NoSQL replaced tradition relational databases
 Performance is the key feature
 Importance of benchmarks
 Top three NoSQL data base’s performance tested
 Cassandra outperforms all the other NoSQL data bases
 Decide based on application

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Einrichtung Titel des Vortrages 40