Ditching the Middleware

David Wood3 Round Stones

david@3roundstones.com

NoSQL Now! 2011

#nosql, like organic food, is defined by what it doesn't contain.

Comparing noSQL solutions is like comparing organic apples and

oranges...

Eric van der Vlist@evlist

25 July 2011

Agenda

• An architecture for communal, horizontal scaling

• Efficiency improvements over other architectures

• Multi-party participation

Three Tier Architecturel Separable tiers; easy to replace

l Separation allows for load balancing of tiers

l Secure database independently

Data Access Business Logic Presentation Logic

Data model changes effect all tiers:• your presentation• your processing model• your data schema.

Scaling OptionsVertical

Horizontal

Vertical Scaling Limits

• July 2011 (changes constantly):

• Amazon EC2: 68 GB RAM

• Rackspace Cloud: 16 GB RAM

• Custom build: M5000 with 512GB RAM

(CPU and disk harder to quantify/compare)

Horizontal Scaling Limits

vs.

Data throughput Optimistic reads?

ChoicesData Access

Business Logic

Presentation Logic

View Model

Controller

Choices

View Model

Controller

< >Objects

l Open Source community project to build a Linked Data Management System

l Visit callimachusproject.org

Callimachus

HTTP GETrequest

Class

Viewable

XMLtemplate apply.xsl

HTML

SPAR

QL

quer

y

RD

F re

spon

se

HTTPresponse

Web serverRDF Store

Resource

Controller

TemplateEngine

Data-View-Controller

ModelView

Controller

< >

View Templates

• Written in XHTML+RDFa (declarative pattern);

• Parsed to create SPARQL queries;

• Query results are filled into the same template.

RDFa queries

Results fill into template

Some (Single System) Advantages

• Minimal abstraction between interface and data (speed, fewer points of failure)

• Minimized queries per page: O(1), not O(n)

• Maximize caching opportunities due to small data elements

• Native optimistic reads

Some (Multi System) Advantages

• Each node has its own store (reduced contention)

• Mirroring of data segmentations for write control

• Theoretical ability to combine data from multiple writes; eventual consistency (RDF as fifth normal form with sufficient provenance information; currently unimplemented)

Case Study:Persistent URLs

Persistent URLs

• Redirection service via HTTP 3xx redirects

• purl.org operated by OCLC since 1995

• Supposed to be “persistent”PURL

Service

WebService

HTTP GET

302 (Found)

HTTP GET

200 (OK)

client

e.g.

Persistent URLs at US GPO

Data Master

Data Slave

DynamicDNS

Normal Ops

Failover /Spillover

PURL Federation

DynamicDNS

Normal Opsfor A.org

e.g. Failover /Spilloverfor A.org

Write-Segmenteddata source

PURL Servicesby different parties

A.org

B.com

C.net

PURL Federation

DynamicDNS

Normal Opsfor C.net

to any host

PURL Servicesby different parties

A.org

B.com

C.net

Callimachuscallimachusproject.org

Persistent URLspurlz.org

Thanks to:

• http://www.flickr.com/photos/vialetter/254383430/

• Callimachus and PURL contributors and sponsors, especially James Leigh

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