Upgrade to PRO for Only $50/Year—Limited-Time Offer! 🔥
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
64
Designing APIs for Data Driven Systems
tareqabedrabbo
0
59
Things I wish I'd known before I started with Microservices
tareqabedrabbo
0
670
Building a Scalable Event Service with Cassandra: Design to Code
tareqabedrabbo
1
480
The 7 Deadly Sins of Microservices
tareqabedrabbo
7
1.2k
The Ubiquitous Graph
tareqabedrabbo
0
210
The 7 Deadly Sins of Microservices
tareqabedrabbo
0
620
Building a Scalable Event Service with Cassandra: Design to Code
tareqabedrabbo
0
88
Time Series and Events: Storage and Querying Strategies with Cassandra
tareqabedrabbo
0
310
Other Decks in Technology
See All in Technology
Entity Framework Core におけるIN句クエリ最適化について
htkym
0
110
Amazon Bedrock Knowledge Bases × メタデータ活用で実現する検証可能な RAG 設計
tomoaki25
6
2.2k
Identity Management for Agentic AI 解説
fujie
0
440
最近の生成 AI の活用事例紹介
asei
1
100
Amazon Connect アップデート! AIエージェントにMCPツールを設定してみた!
ysuzuki
0
130
MariaDB Connector/C のcaching_sha2_passwordプラグインの仕様について
boro1234
0
1k
_第4回__AIxIoTビジネス共創ラボ紹介資料_20251203.pdf
iotcomjpadmin
0
130
日本Rubyの会: これまでとこれから
snoozer05
PRO
5
230
SQLだけでマイグレーションしたい!
makki_d
0
1.2k
SREが取り組むデプロイ高速化 ─ Docker Buildを最適化した話
capytan
0
130
"人"が頑張るAI駆動開発
yokomachi
1
110
Agent Skillsがハーネスの垣根を超える日
gotalab555
6
3.9k
Featured
See All Featured
Pawsitive SEO: Lessons from My Dog (and Many Mistakes) on Thriving as a Consultant in the Age of AI
davidcarrasco
0
37
世界の人気アプリ100個を分析して見えたペイウォール設計の心得
akihiro_kokubo
PRO
65
35k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
37
6.2k
Paper Plane (Part 1)
katiecoart
PRO
0
1.9k
Ten Tips & Tricks for a 🌱 transition
stuffmc
0
34
Collaborative Software Design: How to facilitate domain modelling decisions
baasie
0
97
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
5.8k
brightonSEO & MeasureFest 2025 - Christian Goodrich - Winning strategies for Black Friday CRO & PPC
cargoodrich
2
65
エンジニアに許された特別な時間の終わり
watany
105
220k
A brief & incomplete history of UX Design for the World Wide Web: 1989–2019
jct
1
260
XXLCSS - How to scale CSS and keep your sanity
sugarenia
249
1.3M
Beyond borders and beyond the search box: How to win the global "messy middle" with AI-driven SEO
davidcarrasco
0
22
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!