Graphiti now supports FalkorDB as a graph database backend for multi-agent environments. This integration addresses performance and isolation requirements in production AI agent deployments.
Graphiti builds temporally-aware knowledge graphs that represent evolving relationships between entities over time.
Preston Rasmussen, lead researcher at Zep AI, explains: “What makes Graphiti unique is its ability to autonomously build a knowledge graph while handling changing relationships and maintaining historical context”.
The framework processes both unstructured conversational data and structured business data through its episodic memory architecture. Each fact includes valid_at and invalid_at timestamps, enabling agents to track changes in user preferences and environmental conditions.
Who is Graphiti for?
Developers building multi-agent systems benefit from improved query latency and tenant isolation without architectural changes to existing agent logic. The integration maintains Graphiti’s API surface and temporal data advantages while leveraging FalkorDB’s performance optimizations. Together, this combination ensures context stays relevant, both business-and-time-wise.
This integration is key to solving the following problems:
Agent Knowledge Conflicts
Multiple AI agents accessing shared knowledge graphs without proper isolation put your project, and business, at risk, especially as you scale. FalkorDB’s tenant isolation provides dedicated graph instances per agent while sharing compute resources, eliminating update conflicts without infrastructure duplication costs.
Query Latency Bottlenecks
Knowledge-intensive agents require sub-10ms response times for multi-hop reasoning queries. Graph traversal operations across millions of nodes may exceed acceptable latency thresholds with other graph providers, greatly affecting user experience. FalkorDB’s sparse matrix representation reduces query execution time from seconds to milliseconds, enabling real-time agent interactions.
"The technical architecture supports our episodic memory model efficiently. FalkorDB's tenant isolation implementation enables concurrent agent operations while maintaining the sub-millisecond response times our production deployments require."
Here's how you can take advantage of this
Applications that require memory, context and a smooth user experience are first in line to reap the benefits of this partnership. Here are examples from the field:
Customer Service Agent Fleets
Multiple agents handle concurrent customer interactions requiring access to product catalogs, support histories, and policy databases. Each agent maintains customer-specific context while accessing shared product knowledge. FalkorDB prevents agents from accessing other customers’ data, thus maintaining privacy while enabling shared product relationship queries, even as your business scales.
Enterprise Knowledge Management
Organizations deploy specialized agents for different departments (HR, legal, engineering) accessing overlapping but restricted knowledge domains. Agents require department-specific views of company knowledge without cross-contamination. FalkorDB’s multi-tenancy ensures compliance boundaries while enabling authorized cross-department knowledge sharing.
Next Steps
This integration demonstrates that multi-agent knowledge graphs require purpose-built database architecture. Generic graph databases create bottlenecks that compound as agent populations scale. The Graphiti partnership proves that proper database design directly impacts agent system viability at enterprise scale.
- Graphiti documentation: https://github.com/getzep/graphiti/blob/main/examples/quickstart/quickstart_falkordb.py
- Project examples: https://github.com/getzep/graphiti/tree/main/examples/podcast
The simplest way to run FalkorDB is via Docker:
docker run -p 6379:6379 -p 3000:3000 -it --rm falkordb/falkordb:latest
How does Graphiti's FalkorDB integration improve multi-agent performance?
What tenant isolation benefits does Graphiti + FalkorDB provide?
Can I migrate existing Graphiti agents to the FalkorDB backend?
References and citations
[1] FalkorDB Multi-Tenancy Documentation: https://www.falkordb.com/blog/falkordb-cloud-cluster-support-on-gcp/
[2] FalkorDB vs Neo4j Performance Benchmarks: https://www.falkordb.com/blog/graph-database-performance-benchmarks-falkordb-vs-neo4j/
[3] Graphiti GitHub Repository: https://github.com/getzep/graphiti
[4] FalkorDB Multi-Tenant Architecture: https://www.falkordb.com/
[5] Zep: A Temporal Knowledge Graph Architecture for Agent Memory: https://arxiv.org/abs/2501.13956
[6] Graphiti Quickstart Examples: https://help.getzep.com/graphiti/getting-started/quick-start
