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Explain advanced database sharding strategies and horizontal scaling in PHP systems.

Updated May 24, 2026

Short answer

Database sharding distributes data across multiple database nodes to achieve horizontal scalability, fault isolation, and high-throughput distributed persistence.

Deep explanation

Vertical database scaling eventually reaches physical limits:

  • CPU bottlenecks
  • memory limitations
  • storage throughput ceilings
  • replication lag
  • lock contention

Sharding solves this by partitioning data across multiple independent databases.

Core goals:

  • horizontal scalability
  • fault isolation
  • parallel processing
  • regional distribution

Sharding strategies:

  1. Range-Based Sharding

Data partitioned by ranges. Example:

  • shard1: users 1–1M
  • shard2: users 1M–2M

Problems:

  • uneven distribution
  • hot shards
  1. Hash-Based Sharding

Hash functions distribute records.…

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