HydraDB

What is HydraDB?

HydraDB is a graph database, released as open source, that runs on top of object storage and targets AI agents that need to follow relationships across documents, chats, code and past decisions. Instead of returning only passages that look similar, it links people, projects and events into one graph so an agent can answer questions such as who owns a project or what is blocking a launch. Query and indexing capacity scale separately from storage, and the engine includes native vector search, so teams can combine graph and vector retrieval. You can self-host it on infrastructure you control, using S3-compatible storage and use existing Neo4j drivers and openCypher queries, or run it on HydraDB Cloud. The cloud plans are Ship at $25 per month minimum usage and Scale at $300 per month minimum usage, plus an Enterprise plan with custom pricing; the open-source edition is described as free forever.

Use cases

• Give AI agents persistent memory
• Build a company knowledge graph
• Serve GraphRAG retrieval
• Connect docs, chats and code into one graph
• Replace stitched vector and graph stores
• Self-host a graph database for AI apps

Who it's for

• AI engineers
• Backend developers
• Agent builders
• Platform teams

Why use HydraDB

• Follows relationships between entities, so agents can answer questions that similarity search alone often misses.
• One layer replaces separate vector, graph, Postgres and filesystem stores for agent context.
• Open-source and self-hostable, with a managed cloud when you prefer not to run it yourself.
• Storage and query capacity scale independently, which helps as the graph grows.

HydraDB features

• Graph database built on object storage
• Native vector search alongside graph traversal
• Self-hosting with S3-compatible storage
• Compatible with Neo4j drivers and openCypher queries
• Import of graphs from other databases
• Ontology engine for building graphs from ingested content
• 100+ app connectors on the Ship and Scale cloud plans
• Advanced logs and monitoring on cloud plans
• Python and TypeScript SDKs plus an API
• Dedicated infrastructure and uptime SLA on Scale

HydraDB integrations

• Neo4j drivers
• S3-compatible storage

How to get started with HydraDB

1. Sign up for HydraDB Cloud or deploy the open-source version on your own infrastructure.
2. Ingest documents, conversations and other data; the ontology engine builds entities and links.
3. Query through the API, SDKs or Neo4j-compatible drivers using graph and vector search together.
4. Feed the retrieved context to your agents and monitor activity in the dashboard.

HydraDB limitations

• Cloud plans carry a monthly minimum usage of $25 (Ship) or $300 (Scale)
• Self-hosted use comes with community support only
• Aimed at engineers building their own context layer, not at non-technical users

HydraDB pricing

HydraDB is open source, so you can use and self-host it for free. Paid plans start at $25 per month, according to the official pricing page on 24 Oct 2026.

HydraDB plans

• Open Source

  Free

  • Self-host on your own infrastructure
  • S3-compatible storage
  • Neo4j drivers and openCypher queries
  • Import graphs from other databases
  • Community support

• Ship

  $25/mo

  minimum usage

  • Fully managed on HydraDB Cloud
  • Storage: $0.50/GB-month
  • Ontology engine: $5 per 1M tokens ingested
  • 100+ app connectors
  • Advanced logs and monitoring

• Scale

  $300/mo

  minimum usage

  • Everything in Ship
  • Dedicated infrastructure
  • Storage: $0.25/GB-month
  • Uptime SLA
  • Private Slack channel
  • SOC 2 and GDPR

• Enterprise

  Custom

  • Deploy in your cloud or a dedicated cloud
  • Dedicated forward-deployed engineer
  • 99% uptime SLA
  • HIPAA BAA

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

HydraDB alternatives

The main HydraDB alternatives listed on Debuly are Mem0, Zep, Cognee, Context Data, Marvin and OpenViking. The table compares pricing and platforms; order is A–Z.

1. 

   Cognee

   Open-source memory engine for AI agents that combines vector search, knowledge graphs and relational storage, with a hosted cloud.

   Developer platformsAutomation and agentsResearch and search
   FreemiumVisit Cognee (official site)
2. 

   Context Data

   InterLock proxy that governs what AI agents can read and write in databases, files and APIs, with redaction and approvals.

   Developer platformsAutomation and agents
   Visit Context Data (official site)
3. 

   Marvin

   Open source Python framework from Prefect for getting structured output from LLMs and building agent workflows from tasks and threads.

   Developer platformsCodingAutomation and agents
   Open sourceVisit Marvin (official site)
4. 

   Mem0

   Memory layer for AI agents and apps, available as an open-source package or a managed platform that keeps user context across sessions.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Mem0 (official site)
5. 

   OpenViking

   Open-source context database for AI agents that stores memory, knowledge and skills as a browsable file system

   Developer platformsAutomation and agentsCoding
   Open sourceVisit OpenViking (official site)
6. 

   Zep

   Managed memory and context platform for AI agents, built on the Graphiti knowledge graph, with Python, TypeScript and Go SDKs.

   Developer platformsAutomation and agents
   FreemiumVisit Zep (official site)

HydraDB FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from framerusercontent.com · fetched 24 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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