Motivation & Objectives
• Motivation
– Databases are used in many applications
– Databases serve for storing data in companies
– Companies hire DB administrators and buy expensive
hardware – there is another solution
– Applications (DB) can be virtualized in the cloud
• Thesis’ objectives
– Survey existing services
– Summarize their properties and compare them
– Experimental evaluation of performance
• Cloud computing
• Database as a Service
• Providers of Database as a Service
• Email, photos
• Delivering hosted services
• Models:
– Infrastructure
as a Service
– Platform
as a Service
– Software
as a Service
Source of the image: http://cs.wikipedia.org/wiki/Cloud_computing
• Private cloud
• Public cloud
• Hybrid cloud
Source of the image: http://http://www.skali.net
Source of the image: http://www.dialogic.com/solutions/Cloud-Communications/Learn/Overview-of-Cloud-Communications.aspx
• On premise
– Own hardware, system, software … - everything
• Virtual machine image
– Database running on one machine – easy migration
– Database running on more machines – difficult migr.
• Database as a Service
– Database running on more machines – easy migration
• SQL-based data model
• NoSQL-based data model
• User
– no expert in administration
– working only with the data
• Vendor – thousands of databases
• High-Availability
–Everytime, everywhere
–Datacenter
• Elasticity
– Scaling
• Back-up
• Security
• Maintenance
• SQL
• Portable
• Pricing -> pay-as-you-go
• No small step
• Cooperation: Cloud service <-> existing system
Source of the image: http://http://www.oracle.com/
Positives Negatives
No hardware Paying for the service while still
having the useless hardware
No administration No management at creating and
storing back-up -> must trust to
provider
No maintenance No management at security features >
must trust to provider
Automatic back-ups Not having the data locally > must
trust to provider
Automatic security features
Automatic failover
• Consider carefully: Positives & negatives
• The components which are moved:
Applications, Data, Middleware (Database)
• Microsoft – Azure SQL Database
– Platform – Microsoft Azure
– Microsoft SQL Server
• Amazon – Relational Database Service
– Amazon Web Services
– Database engine: Oracle, MySQL, PostgreSQL,
Microsoft SQL Server
• Google – Google SQL
• Xeround
• Salesforce
• Standard database system
• Useful and easy solution to run a database
• My future work:
– Google SQL
– Comparison Microsoft Azure, Amazon RDS,
Google SQL
– Measuring the services’ performance