Cover Image for HydraDB x Connectors Hackathon
Cover Image for HydraDB x Connectors Hackathon
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HydraDB
World's leading infra for persistent context & memory
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HydraDB x Connectors Hackathon

Virtual
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About Event

HydraDB Connectors Hackathon

July 31, 6 PM PT → August 7, 6 PM PT · Virtual · $500 in prizes

Discord: Join Discord Server

HydraDB is a context layer for AI agents, combining knowledge, memories, documents, metadata, and relationships across multiple sources.

Challenge

Build a HydraDB project using at least 3 connectors and test how well it handles real cross-source retrieval.

Connectors

  1. Twitter/X

  2. Attio

  3. Slack

  4. Linear

  5. Notion

  6. Gmail

  7. Bigtable

  8. Dropbox

  9. Google Drive

  10. Confluence

  11. Calendly

  12. Google Calendar

  13. Intercom

  14. Jira

  15. PostHog

  16. Shortcut

  17. GitHub

  18. GitLab

  19. Freshdesk

  20. Stripe

use the free account on hydradb.com

What to Build

1. Multi-Connector + Document Ingestion

Ingest the same people, companies, projects, or events across multiple sources.

Example: the same person appears in Slack, Gmail, and uploaded documents. Test whether HydraDB connects those references instead of treating them as separate entities.

2. Difficult Retrieval Questions

Ask questions that require more than basic semantic search:

  • Temporal reasoning

  • Metadata filtering

  • Entity deduplication

  • Knowledge updates

  • Third-party attribution

  • Actor-based queries

  • Thread understanding

  • Multilingual retrieval

  • Multi-hop reasoning

Multi-hop questions are especially valuable. The answer should require multiple HydraDB queries or retrieval steps, not one API call.

Example:

Who filed BUG-123, which project are they working on, and what did they say about the fix in Slack?

3. Latency vs Accuracy Competition

Design ingestion and retrieval that is:

  • Accurate

  • Fast

  • Cheap

Use:

  • Fast queries

  • Thinking queries

  • Metadata filters

The goal is to answer most questions using fast mode, while using thinking mode only when the question actually requires deeper reasoning.

Track:

  • Accuracy

  • Latency

  • Number of HydraDB calls

  • Fast vs thinking usage

  • Estimated retrieval cost

Submission

Include:

  • At least 3 working connectors

  • Document ingestion

  • Difficult cross-source questions

  • Expected vs actual answers

  • Latency and accuracy results

  • A 60-second demo

Judging

Correctness, cross-source reasoning, latency, cost, reproducibility, and developer experience.

How far can you push fast mode without sacrificing accuracy?

Resources

MCP: usecortex/hydradb-mcp
CLI: usecortex/hydradb-cli
Docs: https://docs.hydradb.com

Avatar for HydraDB
Presented by
HydraDB
World's leading infra for persistent context & memory
Hosted By
153 Went