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HydraDB launches a graph-native database for persistent agent memory, raising $6.5 million to replace fragmented RAG workflows

Hybrid NVMe and object storage layers accelerate context delivery.

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Chubby♨️@kimmonismus#1496inAI

For two years the whole conversation was about context window size.

Meanwhile the actual problem never moved: agents don't remember anything between sessions. We kept patching it with RAG and manual context injection and calling that memory.

HydraDB is going at the layer everyone routed around.

One API, sessions that persist, knowledge that compounds across agents. The tell in the $6.5M is who raised it: not a frontier lab. They had the compute to solve persistence and spent it on scaling, so memory became a startup's whole thesis instead of a line item in theirs. Fantastic!

7:25 AM · Jun 1, 2026 · 16.8K Views
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Carlos E. Perez@IntuitMachine

Context engineering is extremely critical for mitigating against hallucinations. However, have you invested enough technical effort to make it damn fast?

I suspect not. HydraDB delivers fast context delivery.

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HydraDB launches a graph-native database for persistent agent memory, raising $6.5 million to replace fragmented RAG workflows · Digg