Introduction to NoSQL Databases

Introduction to
NoSQL Databases
San Diego NoSQL Meetup – Aug 2010
By Derek Stainer
http://nosqldatabases.com

Agenda
Introduction
Objective
Explore NoSQL Databases
Conclusion

Introduction
UCSD Graduate in Computer Science
Java Developer for 10 years
Creator of http://nosqldatabases.com
Curator of NoSQL information

Objective
Deeper dive into each type of NoSQL database
Discuss 1-2 NoSQL databases in each family of databases

NoSQL Taxonomy
Key/Value
Document
Column
Graph
Others
Geospatial
File System
Object

Key/Value Databases
Global collection of Key/Value pairs
Inspired by Amazon’s Dynamo and Distributed Hashtables
Designed to handle massive load
Multiple Types
In memory i.e. Memcache
On Disk i.e. Redis, SimpleDB
Eventually Consistent i.e. Dynamo, Voldemort

Key/Value: Voldemort
Created by LinkedIn, now open source
Inspired by Amazon’s Dynamo
Written in Java
Pluggable Storage
BerkeleyDB, In Memory, MySQL
Pluggable Serialization
JSON, Thrift, Protocol Buffers, etc.
Cluster Rebalancing

Key/Value: Voldemort
Versioning, based on Vector Clocks
Reconciliation occurs on reads.
Partitioning and Replication based on Dynamo
Consistent Hashing
Virtual Nodes
Gossip

Other Key/Value Stores
Other Key/Value Stores
Amazon’s Dynamo
Riak
Redis
Memcache
SimpleDB

Document Databases
Similar to a Key/Value database but with a major difference, value is a document
Inspired by Lotus Notes
Flexible Schema
Any number of fields can be added
Documents stored in JSON or BSON formats
Examples: CouchDB, MongoDB

Sample Document
{
"day": [ 2010, 01, 23 ],
"products": {
"apple": { "price": 10 "quantity": 6 },
"kiwi": { "price": 20 "quantity": 2 }
},
"checkout": 100
}

Document: CouchDB
Development began ~ 2005 by Damien Katz former Lotus Notes Developer
Couch – Cluster Of Unreliable Commodity Hardware
Top level Apache Project
Commercially supported by CouchIO
Licensed under Apache License
Written in Erlang
Documents are stored in JSON

Document: CouchDB [cont’d]
B-Tree Storage Engine
MVCC model, no locking
No joins, primary key or foreign key (UUIDs are auto assigned)
Built bi-directional replication
Can even run offline, come back and sync back changes
Custom persistent views using MapReduce
REST API

Document: MongoDB
Development started in 2007
Commercially supported and developed by 10Gen
Stores documents using BSON
Supports AdHoc queries
Can query against embedded objects and arrays
Support multiples types of indexing

Document: MongoDB [cont’d]
Officially supported drivers available for multiple languages
C, C++, Java, Javascript, Perl, PHP, Python and Ruby
Community supported drivers include:
Scala, Node.js, Haskell, Erlang, Smalltalk
Replication uses a master/slave model
Scales horizontally via sharding
Written C++

Column Family Databases
Each key is associated with multiple attributes (i.e. Columns)
Hybrid row/column stores
Inspired by Google BigTable
Examples: HBase, Cassandra

Column: HBase
Based on Google’s BigTable
Apache Project TLP
Cloudera (certifications, EC2 AMI’s, etc.)
Layered over HDFS (Hadoop Distributed File System)
Input/Output for MapReduce Jobs
APIs
Thrift, REST

Column: Hbase [cont’d]
Automatic partitioning
Automatic re-balancing/re-partitioning
Fault tolerant
HDFS
Multiple Replicas
Highly distributed

Column: Hbase [cont’d]
Lars George

Column: Cassandra
Created at Facebook for Inbox search
Facebook -> Google Code -> ASF
Commercial Support available from Riptano
Features taken from both Dynamo and BigTable
Dynamo – Consistent hashing, Partitioning, Replication
Big Table – Column Familes, MemTables, SSTables

Column: Cassandra [cont’d]
Symmetric nodes
No single point of failure
Linearly scalable
Ease of administration
Flexible/Automated Provisioning
Flexible Replica Replacement
High Availability
Eventual Consistency
However, consistency is tuneable

Partitioning
Random
Good distribution of data between nodes
Range scans not possible
Order Preserving
Can lead to unbalanced nodes
Range scans, Natural Order
Custom
Extremely fast reads/writes (low latency)
Thrift API

Column
Basic unit of storage
Column Family
Collection of like records
Record level atomicity
Indexed
Keyspace
Top level namespace
Usually one per application

Eric Evans

Column Details
Name
byte[]
Queried against
Determines sort order
Value
byte[]
Opaque to Cassandra
Timestamp
long
Conflict resolution (last write wins)

Graph Databases
Inspired by Euler Graph Theory, G=(E,V)
Focused on modeling the structure of the data
Property Graph Data Model
Examples: Neo4j, InfiniteGraph

Sample Property Graph[]
Todd Hoff

Graph: Neo4j
Data Model: Property Graph
Nodes – Person, Place, Thing, etc.
Relationships – Lives, Likes, Owns, etc.
Properties on Both
Primary operation is graph traversal between nodes
Written in Java
Embedded database

Graph: Neo4j [cont’d]
Disk-based
Graph stored in custom binary format
Transactional
JTA/JTS, XA, 2PC, MVCC
Scales
Billions of nodes/relationships/properties per JVM
Robust
6+ years in 24/7 production

Multiple language binds
Jython, Cpython
Jruby (including RESTful API)
Clojure
Scala (including RESTful API)
Uses
Social Graph i.e. Facebook
Recommendation Engines
Financial Audit

Licensed under AGPLv3
Dual Commercial License Available
First server is free
Second server Inexpensive
Commercial support provided by Neo Technologies

Other Graph Databases
Other graph databases
InfiniteGraph
HyperGraphDB
sones

Conclusion

Thank You!

References
NoSQL Databases - Part 1 – Landscape, Vineet Guptahttp://www.vineetgupta.com/2010/01/nosql-databases-part-1-landscape.html
NoSQL for Dummies, Tobias Ivarssonhttp://www.slideshare.net/thobe/nosql-for-dummies
NoSQL Databases, Marin Dimitrovhttp://www.slideshare.net/marin_dimitrov/nosql-databases-3584443
CouchDB vs. MongoDB, Gabriele Lanahttp://www.slideshare.net/gabriele.lana/couchdb-vs-mongodb-2982288
Hbase, Ryan Rawsonhttp://www.slideshare.net/adorepump/hbase-nosql
Introduction to Cassandra, Gary Dusbabekhttp://www.slideshare.net/gdusbabek/introduction-to-cassandra-june-2010
Cassandra Explained, Eric Evanshttp://www.slideshare.net/jericevans/cassandra-explained
Towards Robust Distributed Systems, Eric Brewerhttp://www.cs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf
Cassandra - A Decentralized Structured Storage System, Lakshman, Ladishttp://www.cs.cornell.edu/projects/ladis2009/papers/lakshman-ladis2009.pdf

References [cont’d]
Bigtable: A Distributed Storage System for Structured Data, Google Inc.http://static.googleusercontent.com/external_content/untrusted_dlcp/labs.google.com/en/us/papers/bigtable-osdi06.pdf
Dynamo: Amazon’s Highly Available Key-value Store, Amazon Inc.http://s3.amazonaws.com/AllThingsDistributed/sosp/amazon-dynamo-sosp2007.pdf
HBase Architecture 101 – Storage, Lars Georgehttp://www.larsgeorge.com/2009/10/hbase-architecture-101-storage.html
BASE: An ACID Alternative, Dan Pritchett

http://www.nosqldatabases.com	4161
http://konnaissances.blogspot.com	167
http://www.aalizwel.com	122
http://aalizwel.com	27
http://konnaissances.blogspot.fr	21
http://translate.yandex.net	4
http://translate.googleusercontent.com	4
http://www.techgig.com	2
http://www.konnaissances.blogspot.com	2
http://www.bonweb.fr	1
http://konnaissances.blogspot.be	1
http://static.slidesharecdn.com	1
http://webcache.googleusercontent.com	1
http://konnaissances.blogspot.ca	1
http://cache.baidu.com	1
http://www.google.fr	1

Introduction to NoSQL Databases

by Derek Stainer on Aug 05, 2010

Accessibility

Categories

Upload Details

Usage Rights

16 Embeds 4,517

Statistics

Introduction to NoSQL Databases Presentation Transcript