Amazon Neptune — Technology Profile & Architecture

Core Information

#core_information

Name, description, vendor website, logo, technology type and tags.

Overview & Role

Amazon Neptune is a fully managed graph database service provided by Amazon Web Services (AWS). It supports popular graph models like Property Graph (with Apache TinkerPop Gremlin) and W3C's RDF (with SPARQL), making it suitable for building and running applications that work with highly connected datasets.

Domain Classification & Tags

Database

Performance Profile

#performance_profile

Typical read and write throughput, payload size and processing latency.

Read Performance Profile

Throughput: Thousands to tens of thousands of queries/sec (simple queries), hundreds to thousands of queries/sec (complex graph traversals)

Payload Size: Varies greatly depending on query complexity and graph size; typically hundreds of bytes to several MBs for results

Processing Latency: Low single-digit milliseconds for simple point reads, tens to hundreds of milliseconds for complex graph traversals

Write Performance Profile

Throughput: Thousands to tens of thousands of writes/sec (simple writes/updates), hundreds to thousands of writes/sec (batch operations/complex updates)

Payload Size: Typically hundreds of bytes to several KB per individual write operation (e.g., adding a vertex or edge)

Processing Latency: Low single-digit milliseconds for individual writes, tens to hundreds of milliseconds for batch operations

Architecture Diagram

#architecture_diagram

Reference diagram of the technology's internal architecture.

Component Architecture & Topology

open_in_new Standalone Tab

Features

#features

Catalogued product capabilities and what each one does.

Empirical data for features is currently being compiled in the global catalog.

Typical Use Cases

#typical_use_cases

Scenarios the technology is commonly chosen for.

Empirical data for typical use cases is currently being compiled in the global catalog.

Known Customers

#known_customers

Publicly referenced organisations using the technology.

Empirical data for known customers is currently being compiled in the global catalog.

Known Integrations

#known_integrations

Other products and services it is documented to work with.

Empirical data for known integrations is currently being compiled in the global catalog.

Connectors

#connectors

Directional data connections to other technologies, with direction and maturity.

Empirical data for connectors is currently being compiled in the global catalog.

Reference Architectures

#reference_architectures

Published architectures where the technology is used or mentioned.

No published reference architecture blueprints currently link to Amazon Neptune.

Security Features

#security_features

Built-in security and access-control capabilities.

Empirical data for security features is currently being compiled in the global catalog.

Known Issues

#known_issues

Documented limitations, defects and operational pitfalls.

Empirical data for known issues is currently being compiled in the global catalog.

Guidelines

#guidelines

Recommended practices for adopting and operating the technology.

Empirical data for guidelines is currently being compiled in the global catalog.

Standards & Compliance

#standards_and_compliance

Standards, certifications and control requirements it maps to.

Empirical data for standards & compliance is currently being compiled in the global catalog.

Sources

#sources

Documentation and research references behind the recorded information.

Empirical data for sources is currently being compiled in the global catalog.

Expert Validation

#expert_validation

Whether domain experts reviewed and confirmed the content.

Empirical data for expert validation is currently being compiled in the global catalog.