Understanding conflict resolution and avoidance in PostgreSQL: a complete guide
11 days ago
- #Distributed Databases
- #Conflict Management
- #Postgres
- Bi-directional logical replication in Postgres 16 introduces functionality to replicate data between two tables from different publishers, but it's not implicitly safe for Active-Active clusters.
- Distributed Postgres clusters face challenges like sequence rules, data merging concerns, conflict management, and potential node divergence, which can lead to data loss.
- CAP theorem and PACELC principle explain the trade-offs in distributed databases between consistency, availability, and partition tolerance, with network latency adding complexity.
- Conflicts in distributed Postgres clusters can be categorized into naturally convergent, resolvable, divergent, and phantom conflicts, each requiring different handling strategies.
- Techniques to mitigate conflicts include controlling write targets, using Conflict Resistant Data Types (CRDTs), and implementing key management strategies like sequence offsets or globally unique keys.
- CRDTs help manage numeric column conflicts by applying diffs between incoming and existing values or using custom data types with per-node hidden fields.
- Key management strategies to avoid surrogate key conflicts include sequence offsets, globally unique keys (UUIDs, Snowflake IDs), and global allocations.
- Identity columns in Postgres, while standard SQL, may not be flexible enough for distributed clusters, requiring alternative approaches like explicit sequence usage.
- Divergent conflicts, especially involving DELETE or TRUNCATE, can be mitigated by converting UPDATEs to INSERTs or using soft deletes instead of physical deletions.
- Advanced techniques like tombstone records and leveraging Postgres' MVCC can help manage visibility and prevent divergent conflicts in distributed clusters.