Zep maintains a temporal Context Graph, invalidates outdated facts while preserving history, and assembles prompt-ready Context Blocks. The stronger distinction is that HydraDB exposes the underlying versioned graph database itself. It gives you openCypher queries, snapshot-consistent reads, object-store durability, and independently scalable query and indexing compute.
| Dimension | HydraDB | Zep |
|---|---|---|
| Old facts | Keeps every version as queryable graph state | Keeps outdated facts in its temporal Context Graph |
| Time | Tracks when relationships were written and when they were actually valid | Tracks validity of facts inside its managed temporal graph |
| State history | Can directly query and reconstruct past graph state | Preserves history, but exposes it through Zep’s memory and graph APIs |
| Agent context | Lets you control retrieval, graph traversal, temporal filtering, reranking, and final context | Automatically builds and returns prompt-ready Context Blocks |
| Storage | S3-compatible object storage is the durable source of truth | Data lives inside Zep’s managed Context Lake |
| Scaling | Query nodes and indexers scale independently | Scaling is handled by Zep’s managed platform |
| Graph access | Direct openCypher, Bolt, and HTTPS access to the underlying graph | Graph is accessed through Zep’s graph and memory APIs |
| Infrastructure control | Run the database in your own infrastructure and control the full stack | Zep manages the memory infrastructure for you |
| Best fit | Teams building their own agent memory and context infrastructure at scale | Teams that want a managed memory layer for agents |
// When HydraDB is the better fit //
When teams choose HydraDB over Zep
Zep is a strong fit when the priority is adding durable, temporal memory to an application. Choose HydraDB when you need direct control over the underlying graph infrastructure for operational context connected to source records, versioned for review, and retrieved under a token budget.
Governance lives with the context
HydraDB keeps the records behind an answer connected and reviewable, so teams can trace context back to its source.
Context spans operational systems
Model customers, tickets, documents, incidents, policies, and resolutions as one connected substrate instead of stitching memory to every source system at query time.
Evidence stays queryable over time
Retrieve the relevant state for a decision, inspect how it evolved, and give agents context that remains defensible when facts or relationships change.
Retrieval is built for the response
HydraDB ranks connected and semantic signals together, then assembles only the evidence an agent can use inside its token budget.
Frequently asked questions
What is the main difference between HydraDB and Zep?
Zep is a managed context platform with built-in users, threads, memory ingestion, temporal extraction, and prompt-ready Context Blocks. HydraDB starts lower in the stack as a programmable graph database, giving teams more control over their ontology, graph structure, retrieval logic, and application model.
When should I choose HydraDB instead of Zep?
Choose HydraDB when you want direct database queries and control over storage, indexing, and query compute for a broader context system spanning company knowledge, workflows, ontologies, and agent actions. Zep also supports custom entity and relationship types through its ontology features; HydraDB’s distinction is control over the underlying graph infrastructure.
Is HydraDB just another agent-memory API like Zep?
No. Zep exposes high-level memory APIs that automatically turn conversations and business data into a temporal Context Graph. HydraDB exposes the underlying graph and context infrastructure, so developers can build agent memory on top while also using the same graph for broader application and enterprise context.
How do HydraDB and Zep handle changing information?
Both are designed for temporal context. Zep tracks fact validity and automatically invalidates outdated relationships as new information arrives. HydraDB represents versioned, time-aware graph state and lets applications combine automatic extraction with explicitly supplied entities, relationships, and temporal information.
How is retrieval different in HydraDB and Zep?
Zep automatically assembles token-efficient Context Blocks from its Context Graph and also exposes graph search. HydraDB gives developers more direct control over retrieval, combining semantic search, BM25, metadata filtering, graph traversal, and returned graph paths that applications can assemble into their own agent context.
Build agent context that stays correct over time
Move beyond fast graph queries alone. HydraDB keeps evolving historical state and retrieval logic together so agents receive context they can trust.
