158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.

1. NoSQL
@d_danailov

2. NoSQL
Dimitar Danailov
CTO at 158ltd.com
dimityr.danailov[at]gmail.com
Slideshare.net
Github
YouTube
Founder at VarnaIT

3. Topics Today
● Overview
● Characteristics of NoSQL
● NoSQL Database Types
● MongoDB Database Terms
● MongoDB Installation
● Hadoop
● BigData

8. History
Introduction to NoSQL by Martin Fowler

9. Google I/O 2012 - SQL vs NoSQL: Battle
of the Backends

11. RDBMSs use a table-based
normalization approach to data, and
that’s a limited model. Certain data
structures cannot be represented
without tampering with the data,
programs, or both.

12. Performance falls off as RDBMSs
normalize data. The reason:
Normalization requires more tables,
table joins, keys and indexes and thus
more internal database operations for
implement queries.

14. Impedance
MissMatch

19. Characteristics of
NoSQL

20. non-relational
open-source
cluster-friendly
21st Century
Web
schema-less

21. NoSQL Database Types
● Wide Column Store / Column Families
● Document Store
● Key Value / Tuple Store
● Object Databases
● Graph Databases
● Grid & Cloud Database Solutions
● Multidimensional Databases
● Multivalue Databases

22. Key-values Stores

24. Examples Tokyo Cabinet/Tyrant, Redis,
Voldemort, Oracle BDB
Typical applications Content caching (Focus on scaling to
huge amounts of data, designed to
handle massive load), logging, etc.
Data model collection of Key-Value pairs
Strengths Fast lookups
Weaknesses Stored data has no schema

25. Column Family
Stores

27. Examples Cassandra, HBase, Riak
Typical applications Distributed file systems
Data model Columns → column families
Strengths Fast lookups, good distributed storage of
data
Weaknesses Very low-level API

28. Document
Databases

31. Examples CouchDB, MongoDb
Typical applications Web applications (Similar to Key-Value
stores, but the DB knows what the Value
is)
Data model Collections of Key-Value collections
Strengths Tolerant of incomplete data
Weaknesses Query performance, no standard query
syntax

32. Graph Databases

35. Examples Neo4J, InfoGrid, Infinite Graph
Typical applications Social networking, Recommendations
(Focus on modeling the structure of data
– interconnectivity)
Data model “Property Graph” – Nodes
Strengths Graph algorithms e.g. shortest path,
connectedness, n degree relationships,
etc.
Weaknesses Has to traverse the entire graph to
achieve a definitive answer. Not easy to
cluster.

39. Collection
Like an RDBMS TABLE

40. Document
Like an RDBMS Record or Row

41. Field
Like an RDBMS Column
{ key: value }

42. Installation

50. Strata + Hadoop World 2014

51. Questions ?
Dimitar Danailov
Senior Developer at 158ltd.com
dimityr.danailov[at]gmail.com
Slideshare.net
Github
YouTube
Founder at VarnaIT