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Most Graph Databases Break. TigerGraph Scales.

Build without limits →
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When Graph Data Grows, Most Systems Break

Most graph databases break when data gets big and queries get deep. TigerGraph does not.
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Performance drops at depth

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Batch-based updates

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Re-architecture at scale

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Limited traversal depth

TigerGraph Outperforms the Competition

Tiger Graph Savanna
neo4j Aura

Key Capabilities

Massively parallel processing
Fully distributed DB for scaling
New workspaces deployed on demand
Solution Kits for high-value use cases
Query Language Support: GSQL, OpenCypher, GQL pattern-matching
Cypher
Data connectors for Kafka, Spark, cloud object stores
Partial support
BYOC deployment option
AI-optimized
Tiger Graph Savanna

Key Capabilities
Massively parallel processing
Fully distributed DB for scaling
New workspaces deployed on demand
Solution Kits for high-value use cases
Query Language Support: GSQL, OpenCypher, GQL pattern-matching
Data connectors for Kafka, Spark, cloud object stores
BYOC deployment option
AI-optimized
neo4j Aura

Key Capabilities
Massively parallel processing
Fully distributed DB for scaling
New workspaces deployed on demand
Solution Kits for high-value use cases
Query Language Support: GSQL, OpenCypher, GQL pattern-matching Cypher
Data connectors for Kafka, Spark, cloud object stores Partial support
BYOC deployment option
AI-optimized

Why TigerGraph Wins

Other solutions force you to choose between speed and scale, we deliver both.
A graph compares Neo4j to another product symbolized by an orange dragon logo, showing that as data size and speed increase, performance shifts from Neo4j to the dragon logo. Axes are labeled Scale and Speed.
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Unmatched Speed

10-100x faster than competing graph databases.

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Proven Scale

Handles petabytes of data without performance degradation.

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Additional Advantages

  • Flexible deployment (cloud, on-prem, hybrid).
  • Deep-link analysis (10+ hops vs. comp’s 2-3).
  • Real-time updates (not batch processing).
  • Enterprise-ready security and compliance.
  • Built-in ML and AI integration.