Overview

nx-neptune is a Python library that brings graph analytics to your data lake. Project your data from Amazon S3 Tables, S3 Vectors, Databricks, Snowflake, OpenSearch, and other sources into Neptune Analytics for graph analysis — with results exported back to S3 or persisted as Iceberg tables.

Two interfaces

nx-neptune exposes two distinct interfaces for different use cases:

Graph Over Data Lake (Session Manager)

Run graph algorithms on data that lives in your data lake — without moving it permanently into a graph database. The SessionManager API manages the full lifecycle: create, import, analyze, export, and destroy.

Supported data sources:

Amazon S3 Tables — query Iceberg tables via Athena SQL
Amazon S3 Vectors — project vector embeddings via a custom Athena connector
Databricks Unity Catalog — query via a JDBC-based Athena connector
Snowflake — query via the Athena Snowflake connector
Amazon OpenSearch — project embeddings from OpenSearch indices
Any source accessible through Athena federated queries

→ Session Manager docs

NetworkX Backend

A NetworkX-compatible backend that lets you offload graph algorithm workloads to AWS with no code changes. Use familiar NetworkX APIs to seamlessly scale graph computations on-demand.

import networkx as nx

# Build a small social network
G = nx.DiGraph()
G.add_edges_from([
    ("Alice", "Bob"),
    ("Alice", "Carol"),
    ("Bob", "Carol"),
    ("Carol", "Dave"),
    ("Dave", "Alice"),
])

# Run PageRank on Neptune Analytics
scores = nx.pagerank(G, backend="neptune")

# Who's most influential?
top = sorted(scores.items(), key=lambda x: x[1], reverse=True)
for name, score in top:
    print(f"{name}: {score:.4f}")

→ NetworkX Backend docs

Use cases

Fraud detection — project financial transactions as a graph, run community detection (Louvain) to identify fraud rings
Product recommendation — project product catalogs with vector embeddings, run similarity search to find related items

Notebooks

Interactive Jupyter notebooks demonstrate each feature:

Category	Notebooks
Algorithm demos	PageRank, BFS, Degree, Closeness, Louvain, Label Propagation
Data lake	S3 Tables, S3 Vectors, Databricks, Snowflake, OpenSearch
Session management	SessionManager, Instance lifecycle