HydraDB vs Zep
A Zep alternative for
agent memory
Zep maintains a temporal Context Graph, invalidates outdated facts while preserving history, and assembles. 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Keeps outdated facts in its temporal Context Graph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 memory must become governed operational context: connected to source records, versioned for review, retrieved under a token budget, and ready to support decisions across complex workflows.
Governance lives with the context
HydraDB keeps the records behind an answer connected and reviewable—so teams can trace context back to its source rather than treating memory as an opaque application layer.
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 memory is only one part of a broader context system spanning company knowledge, workflows, ontologies, and agent actions. It is better suited when you want to define your own entities, relationships, data boundaries, and retrieval behavior instead of adopting a predefined memory abstraction.
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.
