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@hydra_db

HydraDB

@hydra_db
HydraDB is a graphDB built on object storage: fast, extremely cheap, and purpose-made for use cases like AI memory, ontologies, and company brain.
San Francisco
hydradb.com
Joined August 2025
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  • @hydra_db
    HydraDB
    @hydra_db
    Aug 14
    Hardest part of getting an agent into production, honestly:
    Stale context & no flags8.3%
    Graph/Schema breaks25%
    Retrieval at scale16.7%
    Cold start/Context bloat50%
    24 votesFinal results
  • @hydra_db
    HydraDB
    @hydra_db
    Aug 13
    "Company brain" is currently three different products wearing one name. Enterprise search indexes documents and finds them. A knowledge base stores documents and organises them. Both are genuinely useful, and neither can answer "how does the customer named in this doc relate to
    Image
  • @hydra_db
    HydraDB
    @hydra_db
    Aug 12
    The graph-engineering conversation and the company-brain conversation are the same conversation, and almost nobody is treating them that way. Agent graph: nodes are agents, edges route work, shared state flows along the edges. The part that gets glossed over every time is where
    Image
    00:00
  • @hydra_db
    HydraDB
    @hydra_db
    Aug 7
    We ran LongMemEval-s. 90.79% overall. The two numbers we actually cared about: Knowledge Update 97.43%, Temporal Reasoning 90.97%. Here is why those two, and where we are still soft.
    Image
  • @hydra_db
    HydraDB
    @hydra_db
    Aug 6
    A customer moved last week. Your DB now holds their old address, their new address, two orders shipped to the old one, and a support thread about the move. Every row is relevant. One address is correct. Similarity search gets you to the right topic. It cannot tell you which
    Image
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