What are Redis data migration techniques between versions?

Redis data migration ensures smooth transitions between versions, environments, or infrastructure changes while maintaining data integrity and minimizing downtime.\n\n• **Why Migration is Critical:**\nVersion upgrades, infrastructure changes, performance optimization, disaster recovery, and environment synchronization require careful data transfer.\n\n• **RDB-Based Migration:**\nFastest method for large datasets, creates point-in-time snapshots, minimal network usage, but requires downtime.\n\nBGSAVE # Create snapshot\nscp dump.rdb target_server:/var/lib/redis/\n# Stop target Redis, replace file, restart\n\n• **Replication-Based Migration:**\nZero-downtime approach, real-time synchronization, gradual traffic shifting, ideal for production systems.\n\nREPLICAOF source_host source_port # Set up replication\n# Wait for sync completion\nREPLICAOF NO ONE # Promote to master\n\n• **Live Migration with Dual Write:**\nApplication writes to both instances, gradual read traffic shift, rollback capability, requires application changes.\n\n• **Key-by-Key Migration:**\nMIGRATE target_host target_port key 0 5000\n# Atomic transfer with TTL preservation\n\n• **Python Migration Script:**\nfor key in source.scan_iter(match="user:*"):\n key_type = source.type(key)\n ttl = source.ttl(key)\n \n if key_type == "string":\n value = source.get(key)\n target.setex(key, ttl, value) if ttl > 0 else target.set(key, value)\n\n• **Validation Steps:**\nCompare key counts, sample data verification, performance testing, and application functionality validation.\n\n• **Best Practices:**\nTest in staging first, backup before migration, monitor progress, plan rollback procedures, and validate data integrity post-migration.