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Market/Categories/Developer & AI Platform/HelixDB

Independent product intelligence · Worldwide · 2026-05-01 → 2026-07-31

HelixDBhelix-db.com

HelixDB is a native graph-vector database built in Rust, designed to accelerate development for RAG and AI applications by unifying graph and vector capabilities.

Developer & AI Platformhelix-db.comTracked since 2026-08-211 discovery source
791Backlinks
114Referring domains
23Domain authority
+36.8%Referring domains · 90 days

Authority & distribution

How strong is HelixDB’s web footprint?

Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.

Backlinks

791Current snapshot

Referring domains

114Current snapshot

Authority

23Domain authority · category median 22

90-day move

+36.8%Referring domains, last 90 days
At 23, HelixDB sits above the 22 median for its category.

Trajectory · Pro

The counts above are the latest of 370 daily observations. The curve through them is on the full profile.

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Traffic & engagement

Where HelixDB ranks

Measured · Pro

Measured for this product: global rank and country rank.

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AI referral visibility

Which AI assistants are already sending HelixDB traffic?

Measured · Pro

Measured for this product: AI referral traffic, which assistants refer it and which pages those referrals land on.

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Product profile

What HelixDB is selling.

Traffic makes more sense when you can connect it to the actual product promise.

“HelixDB”

HelixDB is a native graph-vector database built in Rust, designed to accelerate development for RAG and AI applications by unifying graph and vector capabilities.

Developer & AI PlatformSeen 2026-08-21 → 2026-08-21Coverage tier C

What we have measured

4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.

Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.

Canonical website: https://www.helix-db.com

Observed across 1 discovery source.

Research questions

What the evidence answers about HelixDB.

Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.

What problem does HelixDB solve?

HelixDB solves the problem of needing multiple databases for AI memory by providing a single engine that combines knowledge graphs, vectors, temporal awareness, and full-text search. This unified approach is designed for agent memory, RAG, and building company brains.

What features or capabilities does HelixDB offer?

HelixDB offers native knowledge graph modeling, vector recall, temporal awareness, full-text search, GraphRAG retrieval, and a company brain feature. It provides a managed cloud service with a gateway, writer, and reader architecture, and supports type-safe traversals in Rust, Go, TypeScript, and Python.

What is HelixDB?

HelixDB is a native graph-vector database built in Rust, designed to accelerate development for RAG and AI applications by unifying graph and vector capabilities. It is categorized as a Developer & AI Platform tool.

3 of 6 research questions are answered for this product. The rest need source evidence we have not collected yet, so they are left unanswered rather than guessed.

Behind the lock

Unlock full HelixDB intelligence.

  • Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
  • AI referral detailHow much traffic assistants send, which one of them does it, and the page they land on.
  • Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
  • The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.

Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured