Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Surviving Data in Large Doses
Search
Tareq Abedrabbo
November 20, 2013
Technology
0
210
Surviving Data in Large Doses
NoSQL Search Roadshow London 2013
Tareq Abedrabbo
November 20, 2013
Tweet
Share
More Decks by Tareq Abedrabbo
See All by Tareq Abedrabbo
Not a SO(A) Trivial Question!
tareqabedrabbo
0
62
Designing APIs for Data Driven Systems
tareqabedrabbo
0
56
Things I wish I'd known before I started with Microservices
tareqabedrabbo
0
660
Building a Scalable Event Service with Cassandra: Design to Code
tareqabedrabbo
1
470
The 7 Deadly Sins of Microservices
tareqabedrabbo
7
1.2k
The Ubiquitous Graph
tareqabedrabbo
0
200
The 7 Deadly Sins of Microservices
tareqabedrabbo
0
610
Building a Scalable Event Service with Cassandra: Design to Code
tareqabedrabbo
0
81
Time Series and Events: Storage and Querying Strategies with Cassandra
tareqabedrabbo
0
300
Other Decks in Technology
See All in Technology
国産クラウドを支える設計とチームの変遷 “技術・組織・ミッション”
kazeburo
3
1.3k
AIと共に開発する時代の組織、プロセス設計 freeeでの実践から見えてきたこと
freee
4
740
現地速報!Microsoft Ignite 2025 M365 Copilotアップデートレポート
kasada
1
1.2k
[mercari GEARS 2025] Building Foundation for Mercari’s Global Expansion
mercari
PRO
1
140
旧から新へ: 大規模ウェブクローラの Perl から Go への移行 / YAPC::Fukuoka 2025
motemen
3
1k
ECS組み込みのBlue/Greenデプロイを動かしてELB側の動きを観察してみる
yuki_ink
1
120
[CV勉強会@関東 ICCV2025] WoTE: End-to-End Driving with Online Trajectory Evaluation via BEV World Model
shinkyoto
0
270
やり方は一つだけじゃない、正解だけを目指さず寄り道やその先まで自分流に楽しむ趣味プログラミングの探求 2025-11-15 YAPC::Fukuoka
sugyan
2
840
AIエージェントによるエンタープライズ向けスライド検索!
shibuiwilliam
4
560
Dart and Flutter MCP serverで実現する AI駆動E2Eテスト整備と自動操作
yukisakai1225
0
570
明日から真似してOk!NOT A HOTELで実践している入社手続きの自動化
nkajihara
1
830
ステートレスなLLMでステートフルなAI agentを作る - YAPC::Fukuoka 2025
gfx
8
1.3k
Featured
See All Featured
Building a Modern Day E-commerce SEO Strategy
aleyda
45
8.1k
The Cost Of JavaScript in 2023
addyosmani
55
9.3k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
37
2.6k
Large-scale JavaScript Application Architecture
addyosmani
514
110k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
54k
Performance Is Good for Brains [We Love Speed 2024]
tammyeverts
12
1.3k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
31
2.6k
Refactoring Trust on Your Teams (GOTO; Chicago 2020)
rmw
35
3.2k
Evolution of real-time – Irina Nazarova, EuRuKo, 2024
irinanazarova
9
1k
What's in a price? How to price your products and services
michaelherold
246
12k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
24
1.6k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
132
19k
Transcript
Surviving Data in Large Doses Tareq Abedrabbo NoSQL Search Roadshow
London 2013
About me • CTO at OpenCredo • Delivering large-scale data
projects in a number of domains • Co-author of Neo4j in Action (Manning)
What this talk is about…
Supermarkets
Meanwhile, in DevLand
Bob is an application developer
Bob wants to build an application. Bob knows that a
relational database is definitely not the right choice for his application
Bob chooses a NoSQL database because he likes it (he
secretly thinks it’s good for his CV too).
Bob goes for a three-tier architecture. It’s separation of concerns.
It’s best practice.
Bob builds an object model first. It’s Domain Driven Design.
It’s best practice.
Bob uses an object mapping framework. Databases should be hidden
behind layers of abstraction. It’s best practice.
Bob hopes for the best!
What challenges is Bob facing?
Suitability of the data model
Suitability of the architecture and the implementation
Ability to meet new requirements
Being able to use the selected technology to the best
of its ability
Performance
A number of applications built on top of NoSQL technologies
end up unfit for purpose
How did we get ourselves into such a mess?
• Technical evangelism • Evolution in requirements • Unthinking decisions
• Ill-informed opinions
Common problem: there is focus on technology and implementation, not
on real value
So what’s the alternative?
Separation of concerns based on data flow
Data flow
• Lifecycle • Structure • Size • Velocity • Purpose
How?
Identify the concerns: what do I care about?
Identify the locality of these concerns: where are the natural
boundaries?
Build focused specialised models
Compose the models into a complete system
Computing is data structures + algorithms
If we accept that separation of concerns should be applied
to algorithms, it is appropriate to apply the same thinking to data
The real value of this form of separation of concerns
is true decoupling
What’s out there
CQRS
Polyglot Persistence
How do I apply it?
It depends on the data flow :)
For general-purpose data platforms, micro services work well
Build micro services that are closer to the natural underlying
model
Other strategies are possible, for example if the data is
highly volatile, consider in-memory grids
There are practical considerations - obviously
Don’t start with 10 different databases because you think you
might eventually need all of them
How would that impact support and operations?
There is potential for simplification based on clearly targeted usage
Links • Twitter: @tareq_abedrabbo • Blog: http://www.terminalstate.net • OpenCredo: http://www.opencredo.com
Thank you!