Amazon Neptune
by Amazon Web Services
Managed graph database on AWS queried with openCypher, Gremlin or SPARQL over HTTPS endpoints with IAM auth.
- Category
- Cloud & Data Platforms
- Type
- Graph database
- Interface
- REST API
- Built with
- Connect Anything
- Credentials
- AWS access keys
02Data
What you can sync.
- Nodes
- Edges
- Query results
- Graph summary
Put Amazon Neptune nodes next to revenue and usage, so every cost has an owner and a reason.
Need more? Name any other Amazon Neptune data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- AWS access keys
Amazon Neptune uses AWS access keys. You add the credentials once, when the AI asks for them, and it tells you where to create them in Amazon Web Services if you need help.
04How it works
How it works in DataMind.
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Pick Amazon Neptune.
Open Lake, pick Amazon Neptune in the source picker and name the connection. Connect Anything opens with a ready prompt that points the AI at the Amazon Neptune API docs.
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Answer a few questions.
The AI reads the Amazon Neptune documentation, then asks which credentials you will use, which data to sync (for example nodes and edges), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
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Your data lands in Lake.
The connector agent writes a Python connector for Amazon Neptune, tests it against the live API and shows you sample rows. Then the data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
