RICK KRUEGER DAVE VALENTINE @dataogre dataogre.com linkedin.com/in/premie rapps @ingeniousSQL ingeniousSQL.com linkedin.com/in/ingeni oussql RULES OF ENGAGEMENT: NOSQL IS SQL SERVER’S ALLY
RICK KRUEGER
Feb 26, 2016
RULES OF ENGAGEMENT: NOSQL IS SQL SERVER’S ALLY. RICK KRUEGER. DAVE VALENTINE. @ dataogre dataogre.com linkedin.com/in/ premierapps. @ ingeniousSQL ingeniousSQL.com linkedin.com/in/ ingenioussql. Why Rules of Engagement?. - PowerPoint PPT Presentation
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RICK KRUEGER DAVE VALENTINE @dataogre dataogre.com
linkedin.com/in/premierapps
@ingeniousSQL ingeniousSQL.com
linkedin.com/in/ingenioussql
RULES OF ENGAGEMENT:NOSQL IS SQL SERVER’S ALLY
Why Rules of Engagement?
“Directives issued by competent military authority that delineate the circumstances and limitations under which United States forces will initiate and/or continue combat engagement with other forces encountered” - http://ra.defense.gov (JP-104)
Why Rules of Engagement?
“Directives issued by competent military authority that delineate the circumstances and limitations under which United States forces will initiate and/or continue combat engagement with other forces encountered” - http://ra.defense.gov (JP-104)
Why Rules of Engagement?
“Directives issued by competent military authority that Delineate the circumstances and limitations under which United States forces will initiate and/or continue combat engagement with other forces encountered” - http://ra.defense.gov (JP-104)
Why Rules of Engagement?
“Directives issued by competent military authority that delineate the circumstances and limitations under which United States forces will
initiate and/or continue Combat engagement with other forces encountered” - http://ra.defense.gov (JP-104)
AGENDA
NoSQL Family Key Value Column Store Document Databases Graph Databases
Polyglot Persistence Eventual Consistency Wrap Up Questions & Answers
Key Value
SimpleMy Car123
C-4140-9564-5B282124
U.S. Air Force photo
Key Value
Simple
Fast
My Car123
C-4140-9564-5B282124
U.S. Air Force photo
Key Value
Simple
FastScalable
My Car123
C-4140-9564-5B282124
U.S. Air Force photo
Key Value
Simple
FastScalableCheap
My Car123
C-4140-9564-5B282124
U.S. Air Force photo
Key Value
Simple
FastScalableCheapKey Structure
My Car123
C-4140-9564-5B282124
U.S. Air Force photo
We have to wait how long?
Key ValueCouchbase
Adidas, ADP, BMWLinux, Windows, OS Xhttp://www.couchbase.com/
RiakYammer, Best Buy, GithubLinux, OS Xhttp://basho.com/riak/
RedisTwitter, Craigslist, flickrLinux, OS Xhttp://redis.io/
Key Value – When to use
Keys value pairsWeb ComponentsDevice Check-in
Key Value: The Need For Speed BEFORE
100K
AFTER
100K
Cach
e
Column Stores
DoD photo by Petty Officer 1st Class Benjamin D. Olvey, U.S. Navy. (Released)
Column Stores
123455 Car: 626 Year: 2008 Name: Jen Insurance: St Farm
ID Name Insurance Car Year Warrant
y123455 Jen St Farm 626 2008 NULL12356 Bob
12357 John Geico Speed 3 2013 Yes
123456 Name: Bob
123457 Car: Speed 3 Year: 2013 Name: John Insurance: Geico 10
11
12
Type: Oil
Type: Tires
Type: Wipers
Warranty: Yes
ID Type CarID10 Oil 1235711 Tires 12357
12 Wipers 12357
Person_Details Car_Details
Column Stores
ScalableSimple is FastColumn AggregationComplex = Map ReduceComplex can be Slow
DoD photo by Petty Officer 1st Class Benjamin D. Olvey, U.S. Navy. (Released)
Column StoresScalableSimple is FastColumn AggregationComplex = Map ReduceComplex can be Slow
DoD photo by Petty Officer 1st Class Benjamin D. Olvey, U.S. Navy. (Released)
Column StoresScalableSimple is FastColumn AggregationComplex = Map ReduceComplex can be Slow
DoD photo by Petty Officer 1st Class Benjamin D. Olvey, U.S. Navy. (Released)
Column StoresScalableSimple is FastColumn AggregationComplex = Map ReduceComplex can be Slow
DoD photo by Petty Officer 1st Class Benjamin D. Olvey, U.S. Navy. (Released)
Column StoresScalableSimple is FastColumn AggregationComplex = Map ReduceComplex can be Slow
DoD photo by Petty Officer 1st Class Benjamin D. Olvey, U.S. Navy. (Released)
Column StoresHBase
eBay, BlackBerry, ExpediaLinux, OS X, Windows **http://hbase.apache.org/
CassandraFacebook, Shazam, TwitterLinux, OS X, Windowshttp://cassandra.apache.org/
** Additional software is required
HD
Insigh
t
Column Stores: Do I need it…
Unstable Schema
Nullable Columns
Collections
http://www.youtube.com/watch?v=7hfpQMu5xJ0
Document Databases
"That's so crazy that it just might work!"
Document Databases: Planning
http://www.blueangels.navy.mil/
Document Databases: Schemaless?
Document Databases: Not Relational
Trims Table411 1790 Base 118412 1790 John Cooper Works 208413 1790 S 172414 1791 Base 121
Models Table1790 Clubman1791 Countryman1792 Coupe1793 Roadster
Document Databases: NormalizedJSON:
JavaScript Object Notation
Document Databases: Denormalized
Document Databases: Natural
Document Databases: OptionsmongoDB
Craigslist, Foursquare, Shutterfly, IntuitWindows, Linux, and OS Xhttp://www.mongodb.org/
CouchDB (CouchBase)HootSuite, VimeoWindows, Linux, and OS Xhttp://couchdb.apache.org/
RavenDBMSNBC.COM, JetBrainsWindows and Linuxhttp://ravendb.net/
Document Databases
RavenDB Management Studio
Document Databases
CouchDB Futon
You Might Need A Document Database…if your application is document based (eg Content Management, Blogging, User Data Management), or the data isn’t tabular or structured…if you want to archive data, and do not want to deal with schema changes in the archived table…if you are looking for an easier upgrade path or have constant schema churn…if you find yourself using SQL antipatterns, like EAV (Entity-attribute-value)…if programmer friendliness is a big concern
Graph DatabasesRelationships
Nodes PropertiesEdges
RecordsDataPK / FK
2: (Make: Mini, Model: Clubman)
1: (Name: Rick, DOB:20120505)
OWNS:(VIN: 12BA126)
DoD photo by Staff Sgt. Samuel BendetU.S. Air Force (Released)
Graph Databases
Graph Databases
1 | Rick
2 | Dave
3 | Mini
4 | Yugo
Owns
Wants
Wants
Owns
6 | 626
Want
s
5 | Glen
Owns
Wants
http://jalopnik.com/365474/how-about-a-yugo-for-the-24-hours-of-lemons
7 | Brandon
9 | Bob
11 | Nick
8 | S4
13 | A6
10 | M4
12 | Neon
Owns
OwnsWants
Owns
Wants
Owns
Wan
ts
Graph Databases
https://www.facebook.com/about/graphsearch
Graph DatabasesNeo4j
Adobe, Cisco, T-MobileLinux, OS X, Windowshttp://www.neo4j.org/
AllegroGraphNASA, Kodak, PfizerLinux, OS X, Windowshttp://www.franz.com/agraph/allegrograph/
InfiniteGraphCIA, DODLinux, OS X, Windowshttp://www.objectivity.com/infinitegraph
Graph Databases
Graph Databases
Graph Databases
Graph Databases – When to use…
Network
Relationships
Geo
Polyglot Persistence"This is space! Course, we’re just in the beginning part of space, we-we haven’t even got to *outer* space yet!“
– Armageddon (1998)
Polyglot Persistence: Write-Only
Polyglot Persistence: Write Only Graph Database? Key Value? Column Store? Document Database?
Polyglot Persistence: Schema Upgrade
Polyglot Persistence: Archiving
Polyglot Persistence: Cache
OLTP Warehouse
Other Data
Nightly
Nightly
Polyglot Persistence: Cache
Warehouse
Other Data
Version 1
Version 2
Version 3
Polyglot Persistence: 1000 Words
Consistency
Consistency: We want it ALL Speed Availability Scale
Consistency Latency
Consistency: Definitions
N – the number of Nodes (or replicas) that store the dataW – the minimum number of nodes that must acknowledge the Write before considered completeR – the minimum number of Read nodes (or replicas) queried for a read operation
Consistency: Distributed
Replica 1
Replica 2
Replica 3
Consistency: Strong
W+R > N == Strong Consistency
N = 2W = 2 R = 1
Consistency: Strong
W+R > N == Strong Consistency
N = 2W = 1 R = 2
Consistency: Weak
N = 2W = 1 R = 1
W+R <= N == Weak Consistency
Consistency LatencyStrong Weak Low High
Synchronous ReplicationHigh Safety MirroringSynchronous AlwaysOn Availability GroupAsynchronous ReplicationHigh Performance MirroringAsynchronous AlwaysOn Availability Group
Active Secondaries: Readable Secondary Replicas“In many circumstances, data latency between a primary database and the corresponding secondary database is only a few seconds.” -http://msdn.microsoft.com/en-us/library/ff878253.aspx
Consistency: SQL Scale Out
Consistency: Cost
Google search result count = 30 resulted in 20% loss
Amazon, 100ms delays perceptible to users
Speed matters!
Rules of Engagement
Key Value
Column Store
Document
Database
Graph
RDBMS
90% of
Data
Data Size / Scalability
Data
Co
mpl
exity
Remember
Pick the store that matches the shape of your data
Don’t use SQL Server to build Rube Goldberg Machines
If anyone thinks that NoSQL means no planning, they couldn’t be more wrong
Stay informed: NoSQLWeekly.com
Questions?
RICK KRUEGER DAVE VALENTINE @dataogre dataogre.com
linkedin.com/in/premierapps
@ingeniousSQL
ingeniousSQL.com
linkedin.com/in/ingenioussql
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