Migrating from Neo4j to TigerGraph: A Practical Architecture, Data, and Query Playbook

Migrating from Neo4j to TigerGraph involves more than transferring nodes and relationships, requiring organizations to assess dependencies across data models, Cypher queries, application integrations, pipelines, operational tooling, and performance expectations. The proposed six-step process includes documenting the existing architecture, mapping Neo4j labels, nodes, relationships, and properties to TigerGraph types, vertices, edges, and attributes, planning controlled data extraction and validation, reviewing query compatibility, adapting applications, and benchmarking production-like workloads before cutover. TigerGraph’s support for much of openCypher can allow straightforward pattern queries to transition incrementally, while complex analytical, algorithmic, iterative, or performance-sensitive queries may be redesigned in native GSQL. The migration also requires attention to differences in schema rules, query outputs, drivers, APIs, authentication, and data-loading methods, with validation covering both business relationship accuracy and operational performance. Rather than treating the effort as a platform replacement, organizations may use it to redesign graph architectures for larger-scale analytics, real-time use cases, vector and graph search, GraphRAG, fraud detection, supply-chain intelligence, customer analysis, and other connected-data applications.

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