Free Database Audit: comprehensive health report for your database

Learn More

Sound familiar?

  • ▸ Graph model on a whiteboard — the team has the domain knowledge but not the graph-modelling discipline, and the supernode + relationship decisions could lock in pathological queries for years.
  • ▸ Knowledge graph for RAG — vector-only retrieval isn't giving relationship-aware context, and the team is debating Neo4j's hybrid graph+vector approach vs a pure vector DB.
  • ▸ RDBMS → Neo4j migration just got approved and the schema-to-graph mapping is unclear — Postgres tables don't map cleanly to nodes and relationships without thinking about query patterns first.

JusDB Neo4j consultants give you the written graph-architecture document — not a Slack-thread sketch. Book a Neo4j architecture review →

Strategic advisory — not execution

Neo4j Consulting Services

In short: Neo4j consulting is strategic advisory for graph workloads — graph model design, Cypher query strategy, Graph Data Science (GDS) algorithm selection, AuraDB vs self-managed sizing, fraud and knowledge-graph + vector architectures, and RDBMS-to-graph migration planning. You need it before model decisions become irreversible, delivered as written recommendations rather than execution.

Graph model design, Cypher strategy, Graph Data Science algorithm selection, AuraDB sizing, and knowledge-graph + vector hybrid architectures. See the Neo4j hub for the broader services overview.

What our Neo4j consulting covers

Each deliverable is a written decision document, sized topology proposal, or costed trade-off analysis.

Graph Model Design
Node-vs-property modelling, relationship cardinality, supernode mitigation, label hierarchy — written model with the rationale and the query patterns it supports.
Cypher Query Strategy
Traversal patterns for common queries, composite-index design, query-plan tuning via EXPLAIN/PROFILE, hot-pattern caching strategy.
GDS Algorithm Selection
Community detection (Louvain, LP), centrality (PageRank, Betweenness), pathfinding (Dijkstra, A*), embeddings (FastRP, Node2Vec, GraphSAGE) — picked against the workload, not blanket pre-implementation.
AuraDB vs Self-Managed
Tier sizing for AuraDB Professional / Business Critical / Virtual Dedicated, self-managed-on-K8s economics, multi-region placement decisions.
Fraud & Identity Graphs
Transaction-account-device modelling, identity-resolution patterns, suspicious-pattern queries, GDS pipeline for real-time scoring.
Knowledge Graph + Vector
Hybrid RAG architecture — Neo4j native vector indexes + Cypher traversal, embedding-model selection, orchestration between graph and vector retrieval.
RDBMS → Graph Migration
Schema-to-graph mapping, LOAD CSV vs APOC migration tooling, application-tier query rewrites, cutover sequencing with rollback gates.

How a Neo4j consulting engagement is shaped

1–2 weeks
Graph Model Review
Deliverable
Written graph model with rationale, query-pattern audit, supernode mitigation plan, indexing strategy.
When to pick this
Before code ships against the graph model — and before model decisions become irreversible.
1–2 weeks
Migration Strategy
Deliverable
Schema-to-graph mapping, query-rewrite plan, LOAD CSV / APOC migration runbook, cutover sequence.
When to pick this
Before committing to an RDBMS → Neo4j migration timeline.
2 weeks
GDS Pipeline Design
Deliverable
Algorithm selection (community / centrality / pathfinding / embeddings), graph projection design, pipeline orchestration.
When to pick this
Building fraud, recommendation, or knowledge-graph workloads where GDS is the algorithm engine.
2–3 weeks
Greenfield Design
Deliverable
Topology spec, graph model, capacity model, AuraDB / self-managed decision, security baseline, ops runbook outline.
When to pick this
New Neo4j deployment from scratch and you want production patterns from day one.

Neo4j consulting — common questions

Ready to make the call on Neo4j?

Book a 30-minute scoping call. We'll tell you which engagement shape fits and what the deliverable will look like — before any statement of work.