Technology
Neo4j Graph Data Science (GDS)
A high-performance analytics workspace for executing 65+ graph algorithms and machine learning models directly on connected data.
Neo4j GDS transforms raw relationships into predictive insights by running optimized engines (Pregel, Java) over an in-memory graph projection. Data scientists use it to identify hidden clusters via Leiden or Louvain, calculate influence through PageRank, and generate node embeddings for downstream ML pipelines. The library integrates seamlessly with Python via the official GDS client, allowing teams to move from exploratory data analysis to production-grade link prediction or fraud detection without manual feature engineering.
What builders pair with Neo4j Graph Data Science (GDS)
Projects using both technologies. Select a pairing to see a project.
Pairing: Cypher
Graph-Enhanced XGBoost: Beating Fraud Detection Baselines with Neo4j
Pairing: Neo4j
Graph-Enhanced XGBoost: Beating Fraud Detection Baselines with Neo4j
Pairing: Python
Graph-Enhanced XGBoost: Beating Fraud Detection Baselines with Neo4j
Pairing: XGBoost
Graph-Enhanced XGBoost: Beating Fraud Detection Baselines with Neo4j
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