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The Graph Behind Your Agents.
A unified brain to capture working context: interactions, decisions, agent traces, and semantic knowledge.
Learn why we're building HydraDB with object storage. Fast, cheap, and high precision.
$6.5M Raised
Jeff Dean
Researchers from OpenAI and DeepMind
LongMemEval-S Overall
Single Session Recall
Similarity isn't Always relevance.
Similarity search often returns what’s close and not what’s related.
HydraDB connects your context, builds a structured graph, and delivers the exact context agents need.
Relational-first, preference-aware, temporally versioned, precision recall.
Without graphs
Retrieve similar ≠ relevant data
Missed relationships
between concepts, entities, events
Lost agent traces, interactions, user preferences across sessions
Juggling with VectorDB, GraphDB, Postgres with Temporal & filesystems across pipelines
With HydraDB
Make AI stateful with relevant context. Built to compound intelligence.
Get a complete structured view of your knowledge
Personalize results powered by what your agents have learnt from your users
One unified layer combining graphs with all primitives needed to deliver context to AI
Everything you need to Compound Intelligence
High Recall Accuracy
Learn how we lead LongMemEvals with 90%+, BEAM, and FinanceBench.
Accuracy
Scales with your Systems
Designed for high throughput using tiered storage: a hot in-memory cache, NVMe SSD for warm storage, and object storage for cold archival. Context moves fluidly between tiers.
Recall Everything
Assemble context from business data, workplace apps, chat sessions, documents. Remember user preferences while retrieving.
Data
Chat
Preference
Built for Low
Latency Apps
To ensure you can build real time applications with HydraDB
< 200ms
Accuracy vs Context length
HydraDB
VectorDB
Full Context GPT-4o
Architecture Overview
State of the art on various benchmarks
Hydra DB outperforms various context applications on five of six
LongMemEval-s categories. Last updated: March 2026
Category
HydraDB
mem0-oSS
ZEP
Single Session (User)
100.00
38.71
92.90
81.40
Single Session (Assistant)
100.00
8.93
80.40
94.60
Preference Extraction
96.67
40.00
56.70
20.00
Knowledge updates
97.43
52.56
83.30
78.20
Temporal Reasoning
90.97
25.56
62.40
45.10
Multi-session reasoning
76.69
20.30
57.90
44.30
Overall Score
90.79
29.07
71.20
60.20
Frequently Asked questions
What is HydraDB? How is it different from other graph providers?
We are building HydraDB to be the fastest graph layer that acts as the context substrate for your agents. The difference starts at storage. We maintain tiered storage: a hot in-memory cache for actively needed context, NVMe SSD for warm storage, and object storage for cold archival. Context moves fluidly between these tiers based on recency and importance rather than static rules. Frequently accessed context stays fast and immediately available. Older or lower-priority context gets archived cheaply without being discarded. This allows us to make HydraDB extremely fast, cheap, and high precision.
Who is HydraDB for?
Our goal is to unlock the primitives and give you the infrastructure so that you can build your own context stores, company brains, agentic actions for workplace apps, and memory layers on top of HydraDB. In case
How long does integration take?
Under a day for most teams. Drop in our SDK, ingest your first records, and run your first query in under 10 minutes. We provide a forward-deployed engineer for enterprise pilots.
Do I need to replace my existing vector database?
No technical expertise needed since we handle setup, deployment, and ongoing optimization completely
What data sources can I connect?
Agent logs, documents, user memories, knowledge from app sources. Anything that helps you create a complete context substrate for your AI.
How does pricing work as I scale?
You pay for knowledge stored and queries served. Start free, upgrade when your usage grows.
Is HydraDB SOC 2 compliant?
Yes. We are SOC 2 and ISO 27001 certified. Self-hosting is available on the Scale plan for teams with strict data residency requirements.
