1. AWS Sydney Meetup 2012
• Agenda
– Introductions
• 18.00 – 20.00
• First Wednesday of the month
• Takers on Co Organizing meetup group
• Future presentations
– Presentations
• Introduction to NoSql - Darrell King, AWS Architect
• EMR and Dynamo DB – Sohail Khan, AWS/Salesforce Consultant
– Q&A Session

2. NoSQL Definition
• NoSQL is a broad class of database that differs
from the classic RDBMS in some significant
ways, most important being they do not use
SQL as their primary query language.
– NOSQL means Not Only SQL, as in: in the future,
our backends will consist of Not Only SQL
databases but also key-value stores, graph
databases and more.

3. NoSQL Drivers
• Google, Facebook and Twitter
– Real time data out of large volumes of data
– Performance and Real Time more important then consistency
• RDBMS Problems
– Inability to scale
– Demands of big data and elastic provisioning
• Big Data
– Big data is a term applied to data sets whose size is beyond the
ability of commonly used software tools to capture, manage,
and process the data within a tolerable elapsed time. Big data
sizes are a constantly moving target currently ranging from a
few dozen terabytes to many petabytes of data in a single data
set.

4. NoSQL
• NoSQL is all about scalability
– Scaling to size
– Scaling to complexity
• Deliver Heavy R/W workloads.
• Eventual consistency

5. NoSQL
– Eric Brewer’s CAP theorem says that if you want
consistency, availability, and partition tolerance,
you have to settle for two out of three. (For a distributed
system, partition tolerance means the system will continue to work unless there is
a total network failure. A few nodes can fail and the system keeps going.)
– Consistency means that each client always has the same view of the data.
– Availability means that all clients can always read and write.
– Partition tolerance means that the system works well across physical network
partitions.

7. Emerging Categories of NoSQL
1. key-stores without an explicit data model
– many based on Amazon's Dynamo key-value store.
2. Others influenced by Google's BigTable
database
– which supports Google products such as Google Maps and Google
Reader.
3. Document databases store highly structured
self-describing objects
4. Graph databases store complex relationships
– such as those found in social networks.

8. http://blogs.neotechnology.com/emil/2009/11/nosql-scaling-to-size-and-scaling-to-complexity.html

9. Changing Landscape

10. Amazon DynamoDB
• Fully managed NoSQL database
• Released January 18th 2012
• Service based on throughput rather then
storage
• HW – SSD allow predictable performance
Also interesting that they mentioned hardware at all!!
• Similar to managed version of Cassandra

11. Amazon DynamoDB
• Consistency
– DynamoDB writes are always consistent
– Reads are consistent, or eventually consistent
• Durability
– All writes occur to disk, not memory
– A write is only committed once it exists in at least two
physical data centers
• Availability
– Regional Service
– Spans multiple AZ’s
– All data continuously replicated to multiple AZ’s

12. Amazon Elastic MapReduce
• Aim
– Process vast amounts of data
• Hosted
– Hadoop framework (Clusters) (hive)
– EC2 and S3
• Examples
– Web Indexing, Data mining, Log file analysis

13. Elastic MapReduce with DynamoDB
• Seamless Integration
• Complementing technologies
• Managing, analysing and monetising Big Data
• What it fixes
– Cost of admin, maintenance and upfront costs
– Effortless scalability

14. Source/Further Reading
• NoSQL Ecosystem
– http://blog.nahurst.com/visual-guide-to-nosql-systems
• NOSQL: scaling to size and scaling to complexity
– http://blogs.neotechnology.com/emil/2009/11/nosql-scaling-to-size-and-scaling-to-
complexity.html
• Google: MoreSQL is Real
– http://williamedwardscoder.tumblr.com/post/16399069781/google-moresql-is-real
• Visual Guide to NoSQL Systems
– http://blog.nahurst.com/visual-guide-to-nosql-systems
• Brewer’s Keynote
– http://www.cs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf
• Overview of NoSQL
– http://youtu.be/sh1YACOK_bo

15. Source/Further Reading
• CAP Theorem
– http://mysqlha.blogspot.com.au/2010/04/cap-theorem.html
• Plain English Intro to CAP Theorem
– http://ksat.me/a-plain-english-introduction-to-cap-theorem/
• Availability and Partition Tolerance
– http://ksat.me/a-plain-english-introduction-to-cap-theorem/
• Nancy Lunch’s 2002 SIGACT paper proving CAP theorm
– http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.20.1495&rep=rep1&type=p
df
• NOSQL for Dummies
– http://www.slideshare.net/thobe/nosql-for-dummies