Skip to content
_CORE
AI & Agentic Systems Core Information Systems Cloud & Platform Engineering Data Platform & Integration Security & Compliance QA, Testing & Observability IoT, Automation & Robotics Mobile & Digital Banking & Finance Insurance Public Administration Defense & Security Healthcare Energy & Utilities Telco & Media Manufacturing Logistics & E-commerce Retail & Loyalty
References Technologies Blog Know-how Tools
About Collaboration Careers
CS EN DE
Let's talk

Sharding Strategies

05. 02. 2018 Updated: 27. 03. 2026 1 min read advanced
This article was published in 2018. Some information may be outdated.

Architecture Expert

Sharding Strategies

ShardingDatabaseScaling 3 min read

Horizontal data partitioning. Hash, range, consistent hashing.

Strategies

  • Hash: shard = hash(key) % N — even distribution, but requires re-hash on changes
  • Range: A-M to shard 1, N-Z to shard 2 — range queries, risk of hot spots
  • Consistent Hashing: minimizes data movement

Challenges

  • Cross-shard queries are expensive
  • Rebalancing requires migration
  • Bad shard key = hot spots
  • ACID across shards is complex

Summary

Sharding is a last resort. First: optimize queries, indexes, read replicas, vertical scaling.

Need Help with Implementation?

Our team has experience designing and implementing modern architectures. We’re happy to help.

Free Consultation

Share:

CORE SYSTEMS team

We build core systems and AI agents that keep operations running. 15 years of experience with enterprise IT.