HelixDB / LinkedIn · Jun 2026
HelixDB celebrated crossing 5,000 GitHub stars and thanked its community, angels, investors, and Y Combinator.
The fastest & most scalable graph-vector database on the market
Public company, workplace, funding, and market signals
Updated Jul 30, 2026
HelixDB is an open-source graph-vector database for AI memory, GraphRAG, RAG, and “company brain” workloads. It combines knowledge graphs, vector recall, temporal/full-text search, and a managed cloud offering aimed at teams building AI retrieval systems and agent infrastructure.
Primary product
Helix Cloud: an object-storage-backed graph-vector database with integrated vector search, full-text search, and graph traversal for AI memory and RAG.
Founded
2025
Headquarters
San Francisco, California, United States
Team size
1-10 employees
Industry
Software Development
Sub-industry
Graph-vector database / AI infrastructure
Offices
0 jobs at HelixDB
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Business model
Stage
Seed
Total raised
$500K
Latest round
Seed · Jul 2025
Latest amount
$500K
Jul 2025
Investors
Public materials emphasize a small, performance-focused, open-source, community-driven engineering culture. The company highlights Discord, GitHub, X, and a blog with technical posts and benchmarks, but no formal employee benefits or culture page was found.
Pricing
Usage-based for GA Cloud (billed hourly by vCPU and RAM) and SKU-based hourly pricing for enterprise clusters, plus storage and egress charges.
Differentiators
Technology
Customers
Competitors
Estimated revenue
$100K-$500K ARR (third-party estimate)
Estimated monthly visits
2.1K
HelixDB / LinkedIn · Jun 2026
HelixDB celebrated crossing 5,000 GitHub stars and thanked its community, angels, investors, and Y Combinator.
HelixDB / LinkedIn · May 2026
HelixDB announced v2 with dynamic JSON queries, a Rust DSL for compiled queries, multiple runtime modes (in-memory, on-disk, object-storage-backed), query-insight tooling, and vectors on both nodes and edges.
HelixDB / LinkedIn · Apr 2026
HelixDB launched Helix Enterprise, describing it as a horizontally distributed graph database designed for scale, lower cost, and distributed infrastructure.
HelixDB Blog · Nov 2025
HelixDB published benchmarks comparing itself with Neo4j and Postgres on graph workloads, claiming large performance advantages on traversal-heavy queries.
Y Combinator · May 2025
Y Combinator highlighted HelixDB as an open-source graph-vector database for RAG and AI applications, co-founded by George Curtis and Xavier Cochran.