HydraDB vs Amazon Neptune
An Amazon Neptune alternative for agent context
Use HydraDB when you want persistent context infrastructure for AI agents instead of assembling it around a managed AWS graph database.
Amazon Neptune is a managed general-purpose graph database inside AWS.
In AWS’s us-east-1 pricing examples, a Standard db.r5.large instance costs $0.348/hour, or $250.56 for a 30-day month. Storage is $0.10/GB-month and I/O is $0.20 per million requests. I/O-Optimized costs $0.4698/hour and $0.225/GB-month, with no separate I/O charge. Two such instances cost about $501 or $677 per 30-day month before storage and other charges.
At the upper storage price, $0.225/GB-month is almost 10× S3 Standard’s $0.023/GB-month. These are storage rates, not a comparison of total service cost; compute, requests, indexes, and other charges also matter.
Neptune can also participate in GraphRAG architectures through Amazon Bedrock, but connectors, temporal context, and broader hybrid recall still have to be assembled around the database. Bedrock Knowledge Bases uses Neptune Analytics for its GraphRAG integration.
HydraDB brings those pieces into the same context layer: workplace ingestion, versioned relationships, graph traversal, semantic search, lexical search, metadata, and recency-aware retrieval.
| Dimension | HydraDB | Amazon Neptune |
|---|---|---|
| Focus | Agent context infrastructure | Managed general-purpose graph |
| Ingestion | Workplace connectors + APIs | Assembled through AWS services; GraphRAG can use S3 |
| Time | Versioned relationships | Application-defined |
| Retrieval | Graph + semantic + lexical + recency | Graph queries; Bedrock GraphRAG with Neptune Analytics |
| Meter | ~$0.023/GB-month S3 Standard storage baseline + separate compute | Standard: instances + $0.10/GB-month + $0.20/M I/O. I/O-Optimized: higher instance rates + $0.225/GB-month; no I/O charge. |
| Best fit | Organization-wide persistent context | Graph applications inside AWS |
Use HydraDB instead of Neptune when you want ingestion, temporal context, retrieval, and the durable graph to operate as one agent-context system.
Build agent context that stays correct over time
HydraDB keeps evolving historical state and retrieval logic together so agents receive context they can trust.
HydraDB
