Lock in $30 Savings on PRO—Offer Ends Soon! ⏳
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Modeling DB @ Cloud Firestore
Search
Yatima-Kagurazaka
December 16, 2017
Technology
2
780
Modeling DB @ Cloud Firestore
push ID: auto ID in Realtime Database
Yatima-Kagurazaka
December 16, 2017
Tweet
Share
More Decks by Yatima-Kagurazaka
See All by Yatima-Kagurazaka
ChromeOS, Firebase - Google I\O ‘18
yatima
0
530
スマートなcronを考案した / lazy cron
yatima
1
5.6k
Firebaseざっくり / GDG Tokyo New Year Seminar 2018
yatima
0
930
Firestoreで負荷試験 (Loadroid by Rocro) / Firebase.yebisu #1
yatima
1
780
大半のウェブサービス/アプリは,Firebaseなら簡単で安いですよ
yatima
2
3.4k
Realtime Databaseのベストプラクティスっぽいやつ
yatima
0
700
Other Decks in Technology
See All in Technology
非CUDAの悲哀 〜Claude Code と挑んだ image to 3D “Hunyuan3D”を EVO-X2(Ryzen AI Max+395)で動作させるチャレンジ〜
hawkymisc
1
170
エンジニアリングマネージャー はじめての目標設定と評価
halkt
0
270
Challenging Hardware Contests with Zephyr and Lessons Learned
iotengineer22
0
170
re:Invent 2025 ふりかえり 生成AI版
takaakikakei
1
190
ガバメントクラウド利用システムのライフサイクルについて
techniczna
0
190
Overture Maps Foundationの3年を振り返る
moritoru
0
170
AI活用によるPRレビュー改善の歩み ― 社内全体に広がる学びと実践
lycorptech_jp
PRO
1
200
意外とあった SQL Server 関連アップデート + Database Savings Plans
stknohg
PRO
0
300
世界最速級 memcached 互換サーバー作った
yasukata
0
330
Kiro Autonomous AgentとKiro Powers の紹介 / kiro-autonomous-agent-and-powers
tomoki10
0
370
新 Security HubがついにGA!仕組みや料金を深堀り #AWSreInvent #regrowth / AWS Security Hub Advanced GA
masahirokawahara
1
1.7k
Microsoft Agent 365 を 30 分でなんとなく理解する
skmkzyk
1
1k
Featured
See All Featured
Product Roadmaps are Hard
iamctodd
PRO
55
12k
The Straight Up "How To Draw Better" Workshop
denniskardys
239
140k
Bootstrapping a Software Product
garrettdimon
PRO
307
120k
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
196
70k
Building Better People: How to give real-time feedback that sticks.
wjessup
370
20k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
The Art of Programming - Codeland 2020
erikaheidi
56
14k
The MySQL Ecosystem @ GitHub 2015
samlambert
251
13k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
46
2.6k
GraphQLとの向き合い方2022年版
quramy
50
14k
We Have a Design System, Now What?
morganepeng
54
7.9k
Agile that works and the tools we love
rasmusluckow
331
21k
Transcript
Modeling DB @ Cloud Firestore Yatima Kagurazaka ://yati.ma
yati.ma/qi Yatima Kagurazaka Minkore CTO MENSAn Physician I like tech,
design, music, etc My PC: Pixelbook(+ VSCode on Kali Linux)
yati.ma/qi Agenda • What is Cloud Firestore • Structure •
Yatima Model
What is Cloud Firestore
So easy but Equal to prod. use and Inexpensive
yati.ma/qi So easy Realtime Offline mode Direct connect to clients
(like Realtime Database)
yati.ma/qi Equal to prod. use Almost no downtime Super scalability
Multi region Strong Consistency Some query support
yati.ma/qi Almost no downtime
“ yati.ma/qi Super scalability you'll get the same performance fetching
1 result from a set of 100, or 100,000,000.
Structure
Collection, Doc, Field
Collection, Doc, Field
A doc is minimum unit at communication
yati.ma/qi A doc is minimum unit Read Write Rule Update
limit: 1/sec Subcollection depth: ≦ 100
All queries are shallow
Query is available only in a collection, so far
For making full use, change a way of thinking
Yatima Model
UniFeed: Supereasy timeline system
None
yati.ma/qi UniFeed: Usage Just query at viewer self ID!
yati.ma/qi UniFeed: Limit Indexes in a document: ≦ 20,000 But
we can batch() (≦ 500)
yati.ma/qi Multi UniFeed Follower: ≦ 10,000,000 (20,000 * 500) ...Actually,
not everyone follow one Probably up to approx. 1M follower in rough estimate
yati.ma/qi Level 2 multi UniFeed Add batch() at Cloud Functions,
more scalable Follower: ≦ 5,000,000,000 (20,000 * 500 * 500) and you can go any level! your bank balance vs Google’s capacity
Twixxer should use it immediately :-P
But wait, how about doc size?
yati.ma/qi UniFeed: Doc size w/ auth.uid: < approx. 600kb (20,000
* 30 chars) w/ pushid: < approx. 300kb (20,000 * 15 chars) ...Actually, not everyone bla bla so at most 30kb, usually 300 or less (realistic!)
Firebase as a Cache (Componentized DB, Virtual DB)
yati.ma/qi General: Write
yati.ma/qi General: Read
yati.ma/qi FaaC: Write Virtual DB
yati.ma/qi FaaC: Read
yati.ma/qi FaaC: Pros Componentized DB Flux-like data flow Explicit communications
Flexibility of DB Faster view
yati.ma/qi Flux architecture
yati.ma/qi General: Data flow
yati.ma/qi FaaC: Flux-like data flow Virtual DB
yati.ma/qi General: Implicit comm. Who are you?
yati.ma/qi FaaC: Explicit comm. I know! Same component
yati.ma/qi FaaC: Cons Need to edit DB/rule occasionally (Build tool
overcome it) Fetch per component
yati.ma/qi FaaC: Background Lower cost to edit DB Component-Based Architecture
Denormalize Trend of static contents CDN
A doc is minimum unit! English is difficult for me!
Fin. ヾ(╹◡╹*)ノ゛ Throw your masakari axe at me! ://yati.ma