TigerGraph

https://www.tigergraph.com/

Parallel graph DB with GSQL/GQL. CoPilot for entity extraction. Free community edition.

At a glance

Type
Massively parallel graph + GSQL
Tier
T1
Created
2021-02
Latest release
not applicable — not OSS
License
not applicable — not OSS
GitHub
not applicable — no GitHub repo
Pricing
Enterprise only
Funding
$105M total Series C · 2021-02

Taxonomy

storage
graph
retrieval
graph-traversal
persistence
long-term
update
overwrite
unit
fact
governance
inspectable
conflict
overwrite

When to use

Optimised for: relationship modeling + reasoning + governance over pure vector

Anti-fit: not for purely-vector or simple-RAG use cases (graph adds setup cost)

Pros & cons

Pros

Strongest at high-cardinality multi-hop queries and parallel graph compute; outperforms Neo4j on certain analytical workloads.

Cons

GSQL is less widely known than Cypher; smaller community and ecosystem than Neo4j.

Claims & capabilities

First to pass LDBC SNB at 1TB benchmark; executed BI workload at 36TB (73B vertices, 534B edges) and 108TB scale; 40x–337x faster than competitors on 2-hop path queries; 1.8x–58x faster data loading; 5x–13x more disk-efficient. Customers in pharma, healthcare, financial services, telecom, government

Technical surface

API surface
REST, GSQL, SDK: Python, Java
Backend storage
custom (native parallel graph)
Deployment
Both
Embedding model
BYO
Multi-tenancy
TigerGraph Savanna SaaS uses logical separation; on-prem deployment for hard tenant isolation
MCP
no first-party MCP adapter published as of 2026-05; community connectors may exist.
A2A
no Google A2A (Agent2Agent) integration documented as of 2026-05.
OpenTelemetry
first-class

Similar systems

Other knowledge-graph platforms in the catalog, ranked by inbound references.

  • Neo4j T1

    Property graph DB with Cypher; native vector search; Aura Agent + MCP server for graph-as-memory. $100M GenAI investment in 2025.

  • Amazon Neptune Analytics T1

    Vector index on graph nodes queryable via openCypher. Mem0 integration GA 2025; Cognee integration for agentic RAG. Combines semantic recall with multi-hop traversal in one managed service.

  • AllegroGraph (Franz) T1

    RDF triple/quad store with RDFS++ / OWL reasoning. v8.4 (May 2025) added an NLQ interface.

  • Apache AGE T2

    openCypher over Postgres. Pairs with pgvector for graph + vector hybrid retrieval. Azure Database for PostgreSQL ships AGE with ai_extension LLM functions for entity extraction directly in SQL.

  • ArangoDB T1

    HybridGraphRAG combines vector search, graph traversal, full-text in one AQL query. ArangoGraphML for ML pipelines; LangChain integration.

  • Dgraph T2

    Vector indexing on any node. Google Gen AI Toolbox integration; LangChain agent orchestration.

Row last verified 2026-05-14. Catalog data is CC-BY-4.0 — see how to read this.