Centralized vs Federated Agent Memory

Quick answer

Centralized memory is easier to govern and debug early. Federated memory scales better across domains and teams, but requires stronger contracts for synchronization and trust.

Decision criteria

Decide using tenancy boundaries, policy/compliance requirements, latency tolerance, consistency guarantees, and operational ownership structure.

Tradeoff breakdown

Centralized memory improves consistency and observability but can become a bottleneck. Federated memory improves local autonomy and resilience but increases reconciliation complexity.

When to choose option A (centralized memory)

Choose centralized memory for early-stage platforms, strict governance needs, or workflows where global consistency matters more than regional autonomy.

When to choose option B (federated memory)

Choose federated memory when domain teams need independent release velocity, data locality constraints are strict, or platform scale makes single-store operations fragile.

Failure modes

Centralized approaches fail when throughput and ownership grow faster than platform controls. Federated approaches fail when schema drift and weak trust boundaries create conflicting truth sources.

Related pages

Soul: Identity and Continuity Layer · Research: Multi-Source Synthesis Swarm · Design Your First Agentic Swarm

Common questions

What is centralized agent memory? One shared memory system stores and serves context for all relevant agents under common governance controls.

What is federated agent memory? Multiple domain-specific memory systems operate independently and synchronize through defined contracts.