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SJSharding v/s partitioning???
#systemdesigninterview #coding #code #google #ai
@sjain.codes
#Sharding
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THComment “blog” & I’ll share the blog link & notes with you in your DM 🤝🏻
(Make sure to follow else automation won’t work)
Topic: Sharding (Blinkit processes thousands of order every minute… Ever thought how their database survives this load?)
Save for your future interviews 📩
#dsa #systemdesign #tech #coding #codinglife
[dsa, system design, sharding, tech]
@thatcodergirlie
830
TA🚀 System Design Made Simple – From Zero to Scalable Systems!
Master the fundamentals of System Design with clean, easy-to-understand notes covering:
✅ High-Level vs Low-Level Design
✅ Scalability & Reliability
✅ Load Balancing
✅ Caching
✅ Database Sharding
✅ CAP Theorem
Perfect for 💻 Developers, 🎯 Interview Prep, and 🚀 Backend Enthusiasts who want to build scalable, production-ready systems.
If you’re serious about cracking system design interviews or building real-world architectures, this is your starting point.
📩 For more please DM me.
#SystemDesign #BackendDevelopment #SoftwareEngineering #TechNotes #CodingLife ScalableSystems DeveloperLife InterviewPrep
@tanya.jobs
61.3K
RADataBase Sharding
Database sharding means splitting a large database into smaller, faster, and independent pieces called shards.
Instead of storing all user data in one place, we divide it based on a sharding key (like user ID).
This helps:
🔹 Queries run faster
🔹 Load gets distributed
🔹 If one shard goes down, others keep working
Perfect for apps with millions+ users.
#backend #coding #engineering #software #techreels #viralreels #virals #javascript #engineer #nodejs #fyp
@rajan.techie
23.5K
GU1. Caching
2. API Gateway
3. Proxy
4. CDN
5. Sharding
6. Message Queue
7. Webhooks
8. Rate Limiting
9. Microservices
10. Auto Scaling
11. Streams
12. Circuit Breaker
Ace your next interview with these concepts. All the best!
#trending #fullstack #backend #fullstackdeveloper #interviewtips #developerinterview #basicconcepts #techconcepts #fyp #explore #techie (Backend concepts basic full stack development developers tools tips and tricks tutorial interviews instructions tech information)
@guviofficial
191.3K
DESystem Design Roadmap for Beginners❤️
I wish I had this roadmap, when I was starting off and had no clue about Systems!
In this roadmap, I take one particular system i.e Instagram and
✅ Break down essential concepts like sharding, message queues, CDN, replication, load balancing, scaling, API Gateway, etc.
✅ Share the best YouTube tutorials for each topic so you can learn practically.
📌 Comment “Systems” to get the full roadmap link!
[DSA, Data Structures , Indiansincalifornia, indiansinusa ,googler, studyabroadlife ,faang, Software Engineer]
#google #softwareengineer #faang #womenintech #interviewprep
@devshree.17
6.8K
COComment "Notes" i will send you the detailed blog for this.
🚀 What is Database Sharding?
Database Sharding = splitting a large database into smaller pieces (called shards) and storing them across multiple servers.
👉 Why it matters:
• Improves performance ⚡
• Handles millions of users
• Scales horizontally (add more servers instead of upgrading one)
• Reduces database load
🧠 Example:
Instead of storing 1 crore users in one DB → split them across 4 databases
Each DB handles a smaller chunk → faster queries & better performance
🔥 Used by companies like Amazon, Netflix, and Instagram to handle massive scale.
💡 One-line:
Sharding = Divide data → Distribute load → Scale infinitely
Follow for more System Design & Backend concepts 🚀
#systemdesign #backenddeveloper #softwareengineering #Java #coding
@codewithmukul
8.7K
SO"Many of our competitors had raised $100M to $200M... But when we looked at them, they were all different versions of sharding and they were all targeting something like 100X improvement over Ethereum..
I think it was actually good that we were undercapitalized because it forced us to focus. A lot of those companies that had no product, but they had hundreds of millions of dollars. I think in their heads, they thought we've got years of runway. We could solve this in five years and it'll be fine... Too much money is rarely a positive thing."
– Solana Co-Founder Raj Gokal
@solana
6.6K
BYDon’t put all your eggs in one basket 🥚 🧺
#sharding #bybit #lingo #cryptolingo #cryptocurrency #database #cryptoart #cryptoworld #cryptoinvestor #cryptotrader #cryptolife
@bybit_official
36.2K
EXPartitioning vs Sharding
#reels #tech #interviewpreparation #trendingreels #viralreeĺs
@exploring_unseen_07_
4.0K
LEYour database was fine - until it wasn't.
One day the queries slow down. Writes start backing up. The single node can't keep up anymore. And suddenly, sharding isn't optional.
But sharding done wrong is worse than not sharding at all 👇
Here are the 10 database sharding strategies powering production systems today:
Range-Based - Distributes data using continuous value ranges like IDs or dates. Simple but can create hot spots.
Hash-Based - Uses hash functions for even data distribution across shards. Great balance, harder to range query.
Directory-Based - A lookup service maps data to shards. Flexible but adds a dependency.
Geo-Based - Partitions data by geographic region. Essential for latency-sensitive global systems.
Functional - Splits data by service or domain responsibility. Clean boundaries, scales independently.
Key-Based - Uses a specific partition key for distribution logic. Predictable and straightforward.
Consistent Hashing - Balances distribution with minimal reshuffling when nodes are added or removed.
Dynamic Sharding - Adapts shards automatically as workload grows. Operationally complex but powerful.
Composite - Combines multiple strategies together. Maximum flexibility, maximum complexity.
Tenant-Based - Separates data by customer or tenant. Perfect for multi-tenant SaaS architectures.
The rule most engineers learn too late:
There's no universally correct sharding strategy.
The right one depends on your query patterns, scale requirements, and team's operational maturity.
Start with the simplest approach that solves your problem.
Optimize when the bottleneck proves it.
Which sharding strategy does your system use? 👇
@learnwithrockybhatia
6.9K
TEThe biggest 🚩 in System Design discussions? Over-engineering. 🛑
It is crazy how many engineers immediately jump to “Consistent Hashing” and “Sharding” for a database that could easily fit on a single modern Postgres instance. 🐘
A single-node DB on good hardware can handle 5 to 10 Terabytes of data effortlessly. When you shard too early, you introduce massive complexity: cross-shard joins become a nightmare and data rebalancing will keep you up at night.
Instead, use this practical progression:
1️⃣ Vertical Scaling (Max out RAM/SSD first)
2️⃣ Read Replicas (Offload your read-heavy traffic)
3️⃣ Table Partitioning (Break down massive tables)
4️⃣ Sharding (ONLY as an absolute last resort!)
Want the exact metrics and scale triggers you need to know?
👇👇
💬 Comment “SCALE” below, and I’ll instantly DM you my 1-Page Database Scaling Cheat Sheet! 📩
Don’t forget to SAVE this reel to revise before your next interview, and follow @techninjaah for more hardcore backend tips! 🥷💻
@techninjaah
✨ #Sharding Discovery Guide
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