HydraDB
Announcement
HydraDB is now open source.
TheGraphAIRunsOn.
GraphDB builds on object storage: 10x cheaper, ultrafast, and purpose-built for modern AI workloads.
Build ontologies, agent memory, company brains, and context graphs.
$6.5M Raised
Jeff Dean
Researchers from OpenAI and DeepMind
Sky9 Capital
What Engineers Are Building With HydraDB
01 AGENT MEMORY
Build in-house memory systems. With your ideas, for your AI.
02 ONTOLOGIES
03 COMPANY BRAIN
04 AGENTIC ACTIONS
05 CONTEXT ENGINEERING
Own your memory layer. No third-party abstraction. No data leaving your stack.
Graphs work better for storing user preferences, past interactions, and agent traces.
Everything you need to Compound Intelligence
High Recall Accuracy
Learn how we lead on LongMemEval-S (90%+), BEAM, and FinanceBench.
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.
State of the art on various benchmarks
HydraDB outperforms various context applications on five of six LongMemEval-S categories. Last updated: March 2026
HydraDB
Total documents ingested
1 Billion+
Recall accuracy
92%
Pricing
Storage-based pricing with minimum commitment. No per-seat, feature, API limits, or infra caps.
Pay for how much context your agents consume.
Free
- Unlimited API calls & tenants
- Multi-tenancy
- Observability & traces dashboard
- Native connectors to apps (coming soon)
Surge
For agents scaling fast in production
- Everything in free, plus:
- Up to 2GB graph storage
- Overage at $0.50/GB/mo
Scale
Making your agents enterprise-ready
- Everything in surge, plus:
- Up to 10GB graph storage
- Overage at $0.25/GB/mo
Enterprise
For teams deploying HydraDB in their own VPC
- BYOC and fully self-hosted
- Dedicated account manager
- Support & Uptime SLAs
Frequently Asked Questions
What is HydraDB? How is it different from other graph databases?
HydraDB is an object-store-native distributed graph database built in Rust, designed to serve as the context layer for AI systems. Unlike traditional graph databases, where storage is tied more closely to database servers or dedicated cluster volumes, HydraDB makes object storage itself the source of truth.
Why use a graph database like HydraDB for AI agents?
A graph database like HydraDB gives AI agents something vector search alone cannot: relationships and state.
Does HydraDB work with GraphRAG?
Yes. HydraDB can be used as the graph database behind a GraphRAG system.
How does HydraDB improve retrieval for AI agents?
HydraDB improves retrieval by combining vector search with graph traversal, exact-match search, and temporal context.