How to choose the right database for your workload

· Category: System Design

Short answer

Database selection depends on the consistency, query complexity, scale, and flexibility requirements of your workload.

Steps

  1. Relational databases excel at complex transactions, joins, and strong consistency.
  2. Document stores like MongoDB fit flexible schemas and hierarchical data.
  3. Key-value stores like Redis provide extreme speed for simple lookups.
  4. Wide-column stores like Cassandra handle massive write throughput.
  5. Graph databases model complex relationships efficiently.

Tips

  • Use polyglot persistence to match each service with the best store.
  • Benchmark candidate databases with realistic data volumes and query patterns.
  • Consider managed services to reduce operational overhead.
  • Plan migration paths since changing databases later is expensive.

Common issues

  • Forcing relational patterns onto document stores and losing flexibility.
  • Using Redis as a primary database and losing data on eviction.
  • Underestimating operational complexity of distributed NoSQL systems.
  • Lock-in to proprietary query languages lacking ecosystem support.

Example

# Consistent hashing for service discovery
import hashlib

def get_node(key, nodes):
    hash_val = int(hashlib.md5(key.encode()).hexdigest(), 16)
    return nodes[hash_val % len(nodes)]

node = get_node('user-123', ['node-a', 'node-b', 'node-c'])

This snippet implements consistent hashing to distribute keys across nodes, a foundational technique in scalable distributed systems.