Database Sharding & Range Partitioning
Horizontally partition massive database tables across multiple database instances using shard keys.
💡 Why It Matters
When a single database server hits CPU, RAM, or 10TB disk limits, horizontal sharding spreads data across 100 servers.
🌐 Real-World Production Usages & Examples
Notion Workspace Sharding
Scenario: Sharding user documents by workspace_id.
Outcome: Isolated tenant data scales horizontally to 50 shards.
✓ When to Use
- •Tables exceeding 1TB or 50,000 write QPS.
- •Global multi-region data residency compliance.
✕ When NOT to Use
- •Small datasets (<100GB) where vertical scaling is cheaper.
🔑 Core Architecture & Rules
- 1Hash-based Sharding hashes shard key modulo N to assign rows evenly.
- 2Range-based Sharding assigns ranges (e.g. A-F, G-M) to shards.
⚖️ Architectural Trade-Off Analysis
Cross-Shard Joins
PROInfinite storage & write throughput scaling.
CONCross-shard SQL joins and distributed transactions are extremely slow.
⚠️ Failure Modes & Mitigations
Hotspot Shard
Celebrity user or active tenant dominates single shard.
Mitigation: Salt shard keys or use composite keys (user_id + date).
🛠️ Example Usages
Reviewed practical implementations and concrete code walkthroughs for Database Sharding & Range Partitioning.
system design problemexecutable tested
High-Concurrency Flash Sale Seat Reservation System
Design a system that handles 100,000 concurrent seat reservations without double booking or crashing the database.
⬡Explore Related Concepts & Guides
Curated technical reading and direct concept relationships.
📖Core Implementation Guides & Patterns(6 resources)
ArticleSQL Partitioning: Range, Hash, List, and Composite Strategies Explained
Read Article →ArticleSystem Design Sharding Strategy: Choosing Keys, Avoiding Hot Spots, and Resharding Safely
Read Article →External ResourceHow do giant systems scale databases when single servers run out of capacity? | Sharding
Read External ↗🔗 Related Concepts
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