comparison report on mysql and postgresql

MALAYSIAN PUBLIC SECTOR

OPEN SOURCE SOFTWARE (OSS)

PROGRAM

COMPARISON REPORT ON

MySQL and PostgreSQL

NOVEMBER 2009

MALAYSIAN PUBLIC SECTOR OPEN SOURCE SOFTWARE INITIATIVE PHASE IIPhase II : Comparison Report On MySQL and PostgreSQL

Copyright

The government of Malaysia retains the copyright of this document.


Table of Contents

SECTION 1 : INTRODUCTION.................................................................................................1EXECUTIVE SUMMARY........................................................................................................2INTRODUCTION....................................................................................................................2DISCLAIMER..........................................................................................................................3

SECTION 2 : COMPARISON / EVALUATION TABLE................................................................4SOFTWARE USE FOR COMPARISON.................................................................................5

SOFTWARE 1 : MySQL.....................................................................................................6SOFTWARE 2 : PostgreSQL..............................................................................................6

COMPARISON OF FINDING..................................................................................................7SECTION 3 : DRUPAL BENCHMARKING...............................................................................17

BENCHMARKING DRUPAL ON POSTGRESQL VS. MYSQL........................................18BENCHMARK SETUP......................................................................................................18DRUPAL SETUP...............................................................................................................18POSTGRESQL CONFIGURATION..................................................................................18CREATING A POSTGRESQL USER AND DATABASE...................................................19MYSQL CONFIGURATION..............................................................................................19RUNNING THE BENCHMARKS......................................................................................20BENCHMARKING METHODOLOGY...............................................................................20

BASH SCRIPT FOR MYSQL.......................................................................................20BASH SCRIPT FOR POSTGRESQL...........................................................................21

MYSQL RESULTS............................................................................................................21POSTGRESQL RESULTS................................................................................................21

SECTION 4 : SUMMARY AND CONCLUSIONS......................................................................22MYSQL AND POSTGRESQL : SUMMARY.....................................................................23MYSQL AND POSTGRESQL : CONCLUSIONS.............................................................23

APPENDIX A.........................................................................................................................24MYSQL AND POSTGRESQL : SPEED............................................................................24MYSQL AND POSTGRESQL : CONCURRENCY OF 1..................................................25MYSQL AND POSTGRESQL : CONCURRENCY OF 5..................................................25

APPENDIX B........................................................................................................................26Result from Apache Benchmark for MySQL with concurrency of 1.................................26Test 1................................................................................................................................26

Test 2............................................................................................................................28Test 3............................................................................................................................30Test 4............................................................................................................................32Test 5............................................................................................................................34

Result from Apache Benchmark for MySQL with concurrency of 5.................................36Test 1............................................................................................................................36Test 2............................................................................................................................38Test 3............................................................................................................................40Test 4............................................................................................................................42Test 5............................................................................................................................44

Result from Apache Benchmark for PostgreSQL with concurrency of 1..........................46


Test 1............................................................................................................................46Test 2............................................................................................................................48Test 3............................................................................................................................50Test 4............................................................................................................................52Test 5............................................................................................................................54

Result from Apache Benchmark for PostgreSQL with concurrency of 5..........................56Test 1............................................................................................................................56Test 2............................................................................................................................58Test 3............................................................................................................................60Test 4............................................................................................................................62Test 5 ...........................................................................................................................64

SECTION 5 : REFERENCES....................................................................................................66REFERENCES.....................................................................................................................67

Index of Tables

Table 1: Features Comparison between MySQL and PostgreSQL..........................................15Table 2: Summary results of concise form................................................................................24Table 3: Data collection using Mozilla Firefox 3.5.x with YSLOW extension...........................25Table 4: Refer to Appendix B....................................................................................................26Table 5: Refer to Appendix B....................................................................................................26


SECTION 1 : INTRODUCTION


EXECUTIVE SUMMARY

A database can be defined as a set of data that has a regular structure and that is organized

in such a way that a computer can easily find the information stored. Database has become

one of the many essential tools to have in running an organization. Data is a collection of

distinct pieces of information, particularly information that has been formatted (i.e., organized)

in some specific way for use in analysis or making decisions. Those data can be organized

and managed using databases.

Nowadays, the emerging of database software has grown rapidly due to the importance of the

database for organizations. We can choose databases ranging from proprietary to open

source database such as MSSQL, MySQL and PostgreSQL. All databases essentially serve

the same purpose of a storing base for collection of associated files, but performance and

reliability might be differ from one another.

In this report, we will present findings on feature comparisons between MySQL and

PostgreSQL, both are Open Source databases. The findings can be used as references for

agencies that want to adopt or implement Open Source databases for internal or external

systems, email server or portal.

INTRODUCTION

Databases are used every day, sometimes without us realizing. They are everywhere. The

most basic example is a telephone book or a library card index. They can store all sorts of

information, from phone numbers to map grids and references, score cards from sports

games, report cards, etc. They allow quick searching and are great for keeping historical data,

for example weather history. Many websites run using a combination of a database and a

CMS (content management system).

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DISCLAIMER

This reports contains elements which are very technical in nature. People reading this

document are expected to have basic database knowledge. All the data manipulation and

information in this document are base on Research and Development done at OSCC

MAMPU.

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SECTION 2 : COMPARISON / EVALUATION

TABLE


SOFTWARE USE FOR COMPARISON

The choice between MySQL and PostgreSQL is a decision many frequently make when

choosing Open Source relational databases management systems. Among many technical

users, MySQL has long been assumed to be the faster but less full-featured of the two

database systems, while PostgreSQL is assumed to be a more densely featured database

system and is often described as an open-source version of Oracle. MySQL is popular stack

among various software projects because of its percieved ease of use, while PostgreSQL has

has a large following among developers comng from an Oracle or traditional SQL Server

backgrounds.

These assumptions, however, are mostly outdated and incorrect. MySQL has come a long

way since in adding advanced functionality while PostgreSQL has dramatically improved its

speed within the last few major releases. Many, however, are unaware of the improvement

and still hold on to stereotypes based on MySQL 4.1 and PostgreSQL 7.4. The current

versions are MySQL 5.1 and PostgreSQL 8.4.

Also, the speed comparisons are mainly between MyISAM and PostgreSQL engines. If the

comparison is between the latest versions of InnoDB and PostgreSQL, PostgreSQL is often

considered faster but no comparison is performed for this report.

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SOFTWARE 1 : MySQL

MySQL is available in both binary and source code form; it may be modified and

redistributed. Its usage terms are regulated by a double GNU General

Public Licence version 2(GPLv2) /proprietary license.

Binaries and source code are available free of charge. As per the GPLv2

licensing terms, any redistribution of the binaries must be accompanied by

the source code from which they are derived, whether original or modified. An exception to

the GPLv2 licensing requirements is made for a few Free Libre Open Source Software

(FLOSS) programs that use MySQL.

Those not wanting to abide to those terms may buy a proprietary license from MySQL

Inc. Support contracts are also available from the same supplier.

MySQL runs on many Unix-like operating systems, is included in most Linux distributions, and

runs natively on Microsoft Windows.

Current stable version: 5.1.x

SOFTWARE 2 : PostgreSQL

PostgreSQL is available in both binary and source code form; it may be

modified and redistributed. Its usage terms are regulated by a Berkeley

Software Distribution (BSD) -like license, that includes no source code

redistribution requirements.

Binaries and source code are available free of charge. Support contracts are available from

many independent firms.

PostgreSQL runs on many Unix-like operating systems, is included in most Linux

distributions, and runs natively on Microsoft Windows since version 8.0. Current stable

version: 8.4.x

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COMPARISON OF FINDING


FEATURES MySQL PostgreSQL

Raw Speed fast when concurrent access

levels are low, and when there

are many more reads than

writes. On the other hand, it

exhibits low scalability with

increasing loads and write/read

ratios (1)

relatively slow at low concurrency

levels, but scales well with

increasing load levels, while

providing enough isolation between

concurrent accesses to avoid

slowdowns at high write/read ratios (1)

Data Compression supports live compression

since version 5.0 with the

ARCHIVE storage engine.

Archive is a write-once, read-

many storage engine, designed

for historical data. It

compresses data up to 90%. It

does not support indexes. In

version 5.1 Archive engine can

be used with partitioning

Support both live compression and

decompression with a fast

compression scheme to fit more

data in an allotted disk space. The

advantage of compressed data,

besides saving disk space, is that

reading data takes less IO, resulting

in faster data reads

Support Multi-

Processor

Yes Yes

Concurrency focuses on scale-out

technologies and the use of off-

the-shelf commodity hardware (1)

scales much better, both in terms of

using up-scale hardware, and

dealing with concurrency (1)

Asynchronous I/O lacks Async support, though

some drivers have been

created to attempt to overcome

this deficiency using Perl and

supports a full fledged

asynchronous API for use by client

applications. It is reported to

increase performance by up to 40%

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Ruby in some cases.

ACID (Atomicity,

Consistency, Isolation

and Durability)

Compliance

Yes(2) Yes (fully compliant)

Ease of use Both have an impressive array of features that increase data

integrity, functionality and performance. The features included in a

database may help improve performance, ease of use, functionality

and stability

Constraints - supports Not-Null, Unique,

Primary Key and Foreign Key

constraints

- doesn't supports the Check

constraint

- supports Not-Null, Unique, Primary

Key and Foreign Key constraints

- supports the Check constraint for a

long time

Default Values NOW() is the only function that

can be used as a default value,

in a MySQL table

allows for any function marked as

IMMUTABLE or STABLE to be used

as the default value for a column

Support Stored

Procedures

Yes Yes

Triggers Yes Yes

Replication and High

Availability

Yes Yes

Data Types - does not have network IP

address data types that

PostgreSQL has but does

provide INET_ATON() and

INET_NTOA() functions to

convert IPv4 addresses to and

- does not have an unsigned integer

data type, but it has a much richer

data type support in several

aspects: standards compliance, the

logically fundamental data type

BOOLEAN, user-defined data types

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from easily stored integers mechanism, built-in and contributed

data types

- allows columns of a table to be

defined as variable-length

multidimensional arrays. Arrays of

any built-in or user-defined base

type, enum type, or composite type

can be created. Arrays of domains

are not yet supported

Support Subqueries Yes

(but in some forms can be a

huge performance liability. This

will be corrected in version 6.0)

Yes

Partitioning • RANGE

• LIST

• HASH

• KEY

• Composite partitioning using

a combination of RANGE or

LIST with HASH or KEY

subpartitions

• RANGE

• LIST

• HASH partitioning is supported

via immutable functions.

Composite partitioning is also

supported

Data Storage Engines • MyISAM (with full text search

function)

• InnoDB (with transactions,

referential, integrity functions

active)

• PostgreSQL can have both full

text search and transactions,

referential by default

Numbers of Data 9 1

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Storage Engines

Supported

(MySQL functionality is

extended via differrent usage of

Data Storage Engines)

(PostgreSQL has many of MySQL's

Data Storage Engines'

functionalities)

Licensing GPLv2 / Proprietary BSD

Maintainer Sun Microsystems PostgreSQL Global Development

Group

Community Support Yes Yes

Database

Administration Tool

(Web Based)

phpMyAdmin phpPgAdmin

Supported Operating Systems :

Windows Yes Yes

Mac OS X Yes Yes

Linux Yes Yes

BSD Yes Yes

UNIX Yes Yes

AmigaOS Yes Yes

Symbian Yes No

Advanced Indexing

Index Type

Hash indexes Only InnoDB and MEMORY

supports Hash indexes

PostgreSQL supports Hash indexes,

though they are never faster than b-

tree indexes

Multiple Indexes MySQL supports multiple

indexes per table and query

since 5.0.

PostgreSQL supports multiple

indexes per query.

Full-Text Indexes MySQL comes with full-text PostgreSQL 8.2 has full text search

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search, but can only be run on

the (not transaction safe)

MyISAM storage engine.

A 3rd party add-on to MySQL,

Sphinx Fulltext Search Engine

allows it to support full-text

searches of InnoDB tables.

in the tsearch2 module.

PostgreSQL 8.3 integrates tsearch2

into the core: "TSearch2, our

cutting-edge full text search tool,

has been fully integrated into the

core code, and also has a cleaner

API."

Partial Indexes MySQL does not support partial

indexes.

PostgreSQL supports partial

indexes:

A partial index is an index built over

a subset of a table; the subset is

defined by a conditional expression

(called the predicate of the partial

index). The index contains entries

for only those table rows that satisfy

the predicate. Partial indexes are a

specialized feature, but there are

several situations in which they are

useful.

One major reason for using a partial

index is to avoid indexing common

values. Since a query searching for

a common value (one that accounts

for more than a few percent of all

the table rows) will not use the index

anyway, there is no point in keeping

those rows in the index at all. This

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reduces the size of the index, which

will speed up queries that do use

the index. It will also speed up many

table update operations because

the index does not need to be

updated in all cases.

Prefix Indexes MySQL supports prefix

indexes. Prefix indexes cover

the first N characters of a string

column, making the index much

smaller than one that covers

the entire width of the column,

yet still provide good

performance characteristics.

With PostgreSQL, prefix indexes

are a particular case of Expression

Indexes

Multi-column Indexes MySQL is limited to 16 columns

per index.

PostgreSQL is limited to 32 columns

per index.

Bitmap Indexes MySQL has no bitmap indexes

but achieves similar

functionality using its

"index_merge" feature. Bitmap

indexes will be introduced with

the Falcon engine.

PostgreSQL supports the ability to

combine multiple indexes at query

time using bitmap indexes.

Expression Indexes Expression Indexes can be

emulated in MySQL by adding

a precomputed column and

using a trigger to maintain it.

PostgreSQL allows you to create

indexes based on expressions

(which may include calls to

immutable functions). This is very

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handy when you have a table with

relatively stable data (not a lot of

inserts / updates) and will often be

running a query which involves an

expensive calculation.

Non-blocking

CREATE INDEX

Dependent on the storage

engine. Some engines (such as

MySQL Cluster and InnoDB

Plugin) support online add/drop

index (no locks taken). If the

engine doesn't support online

add/drop index, a write

exclusive lock is required and

the table copied.

PostgreSQL supports the ability to

create indexes without locking the

table for writes.

Maximum Table Size - 2 GB on Windows

- 2 TB on MacOSX with HFS+

- 4 TB on Linux 2.4+ with

ext3FS

- 16 TB on Solaris with ZFS

32 TB

Maximum Row Size - 65 KB (VarChar / VarBinary)

- 4 GB (LongTEXT /

LongBLOB)

1.6 TB

Maximum Field Size 4 GB 1 GB

Maximum Rows per

Table

Unlimited (with InnoDB) Unlimited

Maximum Columns

per Table

1000 250 – 1600 depending on column

types

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Maximum Indexes per

Table

Unlimited Unlimited

Other Objects:

Data Domain No Yes

Cursor Yes Yes

Trigger Yes Yes

Function Yes Yes

Procedure Yes Yes

External routine Yes Yes

Access Control

Native network

encryption

Yes (with SSL 4.0) Yes

Brute-force protection No No

Enterprise directory

compatibility

No Yes (LDAP, Kerberos)

Password complexity

rules

No No

Patch access Partial (no security page) Yes

Run unprivileged Yes Yes

Security Certification No Yes (EAL1 3)

Table 1: Features Comparison between MySQL and PostgreSQL

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Note (1): Base on Drupal Benchmarking Summary at Section 3

Note (2): For transactions and referential integrity, the InnoDB table type must be used;

Windows installer sets this as default if support for transactions is selected. On other

operating systems the default table type is MyISAM. However, even the InnoDB table type

permits storage of values that exceed the data range; some view this as violating the Integrity

constraint of ACID.

Note (3): Network traffic could be transmitted in a secure way (not clear-text, on general SSL

encryption). In order to have precise option as default, the included options or extra modules

must be purchased.

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SECTION 3 : DRUPAL BENCHMARKING


BENCHMARKING DRUPAL ON POSTGRESQL VS. MYSQL

This article is about performance of Drupal on both MySQL and PostgreSQL.

So, I decided to do a controlled benchmark of Drupal 6 on both databases to see which

database is faster.

BENCHMARK SETUP

For the hardware, I used my notebook, which is an Intel(R) Core(TM)2 Duo CPU T7100 @

1.80GHz, with 3 GB of RAM.

This server runs Ubuntu Desktop 9.10 Karmic Koala i686.

MySQL is 5.1.37-1ubuntu5, and PostgreSQL is 8.4.1-1, which are what comes with this distro

version. PHP is 5.2.10-2ubuntu6.3, with APC (Alternative PHP Cache) 3.0.19-2 installed and

configured.

DRUPAL SETUP

Drupal is the latest 6.14 version from http://ftp.drupal.org/files/projects/drupal-6.14.tar.gz.

The setup was a multisite install, so both sites are running from the same code base. One

was configured for MySQL and one for PostgreSQL.

POSTGRESQL CONFIGURATION

Setting up a PostgreSQL database took some digging, but once the steps are figured out,

they are fairly simple.

No other changes from the default settings provided by Ubuntu are made.

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CREATING A POSTGRESQL USER AND DATABASE

The steps to create a database in PostgreSQL are documented in the INSTALL.pgsql.txt that

comes with Drupal.

However, I used a slightly different approach, with the same end result.

For creating a user and database, assuming we want a user called drupal and a password

of drupal123, you do the following in a shell:

$ sudo bash# su - postgres$ createuser -DRS username$ createdb -O username drupal$ psqlALTER USER USERNAME WITH UNENCRYPTED PASSWORD 'drupal123';

Once the database is created, install drupal6 by executing this command in

terminal:

$ sudo apt-get install drupal6

After finish the installation, visit URL,

http://localhost/drupal6/install.php then proceed with the web base installation and key in the credential about

MySQL and PostgreSQL such as Username, Password, Host, Port and etc so Drupal

will create the tables for you in the database.

MYSQL CONFIGURATION

The default configuration supplied with Ubuntu was used. This has the query cache turned on

by default. All the tables are MyISAM.

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RUNNING THE BENCHMARKS

The benchmark consisted of running two benchmarks using ab on each virtual host.

One benchmark was for a concurrency of 1:

ab -c1 -n1000 http://localhost/drupal6/ (MySQL)

ab -c1 -n1000 http://localhost/drupalpg/ (PostgreSQL)

The other was with a concurrency of 5:

ab -c5 -n1000 http://localhost/drupal6/ (MySQL)

ab -c5 -n1000 http://localhost/drupalpg/ (PostgreSQL)

BENCHMARKING METHODOLOGY

For setting up data for this test, I insert data into database, bash script was used to create

2000 comments and manually add 1 page. Im not using the Drupal's Devel Module to

generate content and pages because its need to amend the default configuration for php.ini .

BASH SCRIPT FOR MYSQL

#!/bin/bash

for i in `seq 1 2000`;

do

echo $i

mysql -usql -e"use drupal6;INSERT INTO comments (pid, nid, uid, subject, comment, hostname, timestamp, status, format, name, mail, homepage) VALUES (0, 1, 1, 'Testing Comment', 'Benchmark Testing Comment 123456', '::1', 1260193872, 0, 1, 'fenris', '', '')"

done

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BASH SCRIPT FOR POSTGRESQL

#!/bin/bash

for i in `seq 1 2000`;

do

echo $i

sudo -u postgres psql -U postgres -d drupal -c "INSERT INTO comments (pid, nid, uid, subject, comment, hostname, timestamp, status, format, thread, name, mail, homepage) VALUES (0, 1, 1, 'Testing Comment', 'Benchmark Testing Comment 123456', '::1',1260193872, 0, 1, '01/', 'fenris', 'mohdfenrisgmail.com', '')"

done

MYSQL RESULTS

MySQL with Drupal's Devel module

When hitting the front page of the site, the MySQL site shows this:

Page execution time was 88.57 ms. Executed 36 queries in 10.73 milliseconds.

POSTGRESQL RESULTS

PostgreSQL with Drupal's Devel module

When hitting the front page of the site, the PostgreSQL site shows this:

Page execution time was 221.52 ms. Executed 38 queries in 102.16 milliseconds.

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SECTION 4 : SUMMARY AND CONCLUSIONS


MYSQL AND POSTGRESQL : SUMMARY

The following table shows a summary of the results in a concise form.

Table 2: Summary results of concise form

MYSQL AND POSTGRESQL : CONCLUSIONS

MySQL was built for speed, to the detriment of everything else. SQL standard features like

transactions, referential integrity and others have been grafted over only after considerable

arm twisting.

However, it is only fast at low concurrency levels, and reports of instability, low robustness

and scalability keep coming out.

PostgreSQL was built strictly following the ACID model, with an emphasis on data integrity

and SQL standard compliance, speed notwithstanding. It then underwent optimizations and

speedups, while at the same time adding new features to its already large set.

Today it is robust, standards compliant and well featured. While still being relatively slow at

low concurrency levels, it scales well with increasing load levels.

The definite conclusion from these benchmarks is that out of the box, MySQL is configured to

run faster than PostgreSQL.

FUTURE CONSIDERATIONS

PostgreSQL can probably be made better by further tuning.

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Database MySQL PostgreSQLTotal time taken for front page (milliseconds) 88.57 221.52Time for front page queries (milliseconds) 10.73 102.16

2260.2 2251.5

25.09 5.54

44.97 11.02

Total time taken for page with 2000 comments (milliseconds)Concurrency of 1 using Apache Benchmark (requests per second) Concurrency of 5 using Apache Benchmark (requests per second)


APPENDIX A

MYSQL AND POSTGRESQL : SPEED

Table 3: Data collection using Mozilla Firefox 3.5.x with YSLOW extension

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Test Database MySQL PostgreSQL

1 2199 2172

2 2418 2412

3 2223 2190

4 2196 2224

5 2381 2379

6 2393 2186

7 2190 2177

8 2199 2200

9 2209 2218

10 2194 2357

Average 2260.2 2251.5

Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)Total time taken for page with 2000 comments (milliseconds)

Total time taken for page with 2000 comments (milliseconds)


MYSQL AND POSTGRESQL : CONCURRENCY OF 1

Table 4: Refer to Appendix B

MYSQL AND POSTGRESQL : CONCURRENCY OF 5

Table 5: Refer to Appendix B

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Test Database

1 25.28 5.49

2 25.55 5.46

3 24.35 5.54

4 25.55 5.62

5 24.73 5.61

Average 25.09 5.54

MySQL PostgreSQLConcurrency of 1 using Apache Benchmark (requests per second) Concurrency of 1 using Apache Benchmark (requests per second) Concurrency of 1 using Apache Benchmark (requests per second) Concurrency of 1 using Apache Benchmark (requests per second) Concurrency of 1 using Apache Benchmark (requests per second)

Concurrency of 1 using Apache Benchmark (requests per second)

Test Database

1 46.57 10.88

2 43.85 11.09

3 44.21 11.01

4 43.86 11.16

5 46.38 10.98

Average 44.97 11.02

MySQL PostgreSQLConcurrency of 5 using Apache Benchmark (requests per second) Concurrency of 5 using Apache Benchmark (requests per second) Concurrency of 5 using Apache Benchmark (requests per second) Concurrency of 5 using Apache Benchmark (requests per second) Concurrency of 5 using Apache Benchmark (requests per second)

Concurrency of 5 using Apache Benchmark (requests per second)


APPENDIX B

Result from Apache Benchmark for MySQL with concurrency of 1

Test 1

This is ApacheBench, Version 2.3 <$Revision: 655654 $> Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/ Licensed to The Apache Software Foundation, http://www.apache.org/

Benchmarking localhost (be patient) Completed 100 requests Completed 200 requests Completed 300 requests Completed 400 requests Completed 500 requests Completed 600 requests Completed 700 requests Completed 800 requests Completed 900 requests Completed 1000 requests Finished 1000 requests

Server Software: Apache/2.2.12 Server Hostname: localhost Server Port: 80

Document Path: /drupal6/ Document Length: 4886 bytes

Concurrency Level: 1 Time taken for tests: 39.555 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 5422000 bytes HTML transferred: 4886000 bytes Requests per second: 25.28 [#/sec] (mean) Time per request: 39.555 [ms] (mean)

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Time per request: 39.555 [ms] (mean, across all concurrent requests) Transfer rate: 133.86 [Kbytes/sec] received

Connection Times (ms) min mean[+/-sd] median max Connect: 0 0 0.0 0 0 Processing: 35 39 5.7 38 90 Waiting: 35 39 5.7 37 90 Total: 35 39 5.7 38 91

Percentage of the requests served within a certain time (ms) 50% 38 66% 39 75% 40 80% 41 90% 45 95% 50 98% 57 99% 70 100% 91 (longest request)

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Test 2

fenris@thinkbuntu:~$ ab -c1 -n1000 http://localhost/drupal6/ This is ApacheBench, Version 2.3 <$Revision: 655654 $> Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/ Licensed to The Apache Software Foundation, http://www.apache.org/




Concurrency Level: 1 Time taken for tests: 39.141 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 5422000 bytes HTML transferred: 4886000 bytes Requests per second: 25.55 [#/sec] (mean) Time per request: 39.141 [ms] (mean) Time per request: 39.141 [ms] (mean, across all concurrent requests) Transfer rate: 135.28 [Kbytes/sec] received

Connection Times (ms) min mean[+/-sd] median max

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Connect: 0 0 0.0 0 0 Processing: 35 39 5.9 37 95 Waiting: 35 39 5.9 37 95 Total: 35 39 5.9 37 95


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Test 3







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Test 4







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Test 5







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Result from Apache Benchmark for MySQL with concurrency of 5

Test 1






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Test 2






Connection Times (ms) min mean[+/-sd] median max Connect: 0 0 0.0 0 0 Processing: 40 114 34.4 112 257

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Waiting: 39 111 33.2 109 248 Total: 40 114 34.4 112 257


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Test 3







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Waiting: 38 111 32.6 109 237 Total: 38 113 33.6 112 243


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Test 4







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Waiting: 37 111 30.8 110 278 Total: 37 114 31.2 114 278


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Test 5







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Waiting: 38 105 29.4 104 205 Total: 38 108 30.0 107 234


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Result from Apache Benchmark for PostgreSQL with concurrency of 1

Test 1




Document Path: /drupalpg/ Document Length: 4881 bytes


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Test 2







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Waiting: 157 183 22.1 176 404 Total: 157 183 22.2 177 409


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Test 3







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Waiting: 157 180 17.7 175 286 Total: 158 181 17.9 175 286


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Test 4







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Waiting: 158 178 14.3 174 278 Total: 158 178 14.4 174 279


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Test 5







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Waiting: 158 178 15.0 174 340 Total: 158 178 15.0 174 340


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Result from Apache Benchmark for PostgreSQL with concurrency of 5

Test 1






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Test 2







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Waiting: 192 446 108.3 445 793 Total: 192 450 109.0 452 793


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Test 3







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Waiting: 176 450 103.7 450 809 Total: 176 454 104.7 453 849


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Test 4







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Waiting: 177 442 112.9 444 874 Total: 177 447 113.2 448 874


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Test 5







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Waiting: 183 450 115.1 452 891 Total: 183 455 115.8 458 891


Prepared by: Khairul Aizat Kamarudzzaman, OSCC MAMPU

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SECTION 5 : REFERENCES


REFERENCES

• David Fetter , PostgreSQL Experts Inc <[email protected]>• Arjen Lentz , Open Query <[email protected]>• MySQL Connection strings • Is MySQL really this bad? - Ars Tehnica • MySQL vs. PostgreSQL (2006-October) • Open Source Database Software Comparison • What to consider when moving from MySQL to PostgreSQL • Comparison Matrix • http://www.jonathanboutelle.com/mt/archives/2005/08/mysql_vs_postgr.html • http://www-css.fnal.gov/dsg/external/freeware/pgsql-vs-mysql.html • http://www.devx.com/dbzone/Article/20743 • Critical comparison as wiki from PhiloVivero (2005) • http://www.odesk.com/blog/2009/06/postgresql-vs-mysql/• http://en.wikipedia.org/wiki/Comparison_of_relational_database_management_systems• http://forge.mysql.com/wiki/Main_Page• http://dev.mysql.com/doc/• PostgreSQL Connection strings • Why PostgreSQL Instead of MySQL: Comparing Reliability and Speed in 2007 • Transactional DDL in PostgreSQL: A Competitive Analysis • PostgreSQL vs MySQL with Rails • http://www.vitavoom.com/postgresql.html • http://article.gmane.org/gmane.comp.lang.ruby.rails/12576 • http://www.sitepoint.com/article/site-mysql-postgresql-1 • http://feedlounge.com/blog/2005/11/20/switched-to-postgresql/ • http://www.postgresrocks.com/ • http://www.postgresql.org/docs/• http://2bits.com/articles/benchmarking-postgresql-vs-mysql-performance-using-drupal-5x.html

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comparison report on mysql and postgresql

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