Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Amazon Neptune is an efficient and dependable graph database service that is fully managed, facilitating the development and operation of applications that handle intricate, interconnected datasets. At its heart, Amazon Neptune features a specialized, high-performance database engine tailored for the storage of billions of relationships while enabling rapid querying with latency measured in milliseconds. It accommodates widely-used graph models, including Property Graph and W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which simplifies the process of crafting queries for navigating complex datasets. This service supports various graph-based applications, including recommendation systems, fraud detection mechanisms, knowledge graphs, drug discovery initiatives, and enhanced network security protocols. With a proactive approach, it enables the detection and analysis of IT infrastructure threats through a multi-layered security framework. Furthermore, it allows users to visualize their entire infrastructure to effectively plan, forecast, and address potential risks, while also enabling the creation of graph queries for the near-real-time identification of fraudulent patterns in financial and purchasing activities, thereby enhancing overall security and efficiency.
Description
Develop your Knowledge Layer through a user-friendly visual interface that facilitates interaction with the knowledge graph. You can create and query this graph while enriching domain concepts with relevant data. By activating bots, you can enhance the knowledge graph with dynamic connections, allowing for a more interconnected experience. The platform also supports the creation and composition of services using functional composition features, enabling users to add and manage services seamlessly within the knowledge graph. It offers both interactive and scripted access to essential system actions, making operations more efficient. Additionally, the system incorporates schema management, data loading, querying, and administrative capabilities. The command line interface can be easily expanded with custom plug-ins, providing developers with the flexibility to introduce new functionalities. Knowledge applications, which are specific use cases developed by clients on the Maana platform, provide AI-driven insights that aid in operational decision-making. Each knowledge application consists of decision models designed to execute real-time calculations tailored to user needs. Importantly, customers are restricted from accessing knowledge applications created by other users, ensuring privacy and uniqueness in their implementations. This approach fosters a dedicated environment where clients can innovate and customize their knowledge solutions.
API Access
Has API
API Access
Has API
Integrations
AWS App Mesh
AWS Marketplace
Amazon Quantum Ledger Database (QLDB)
G.V() Gremlin IDE
KeyLines
KgBase
New Relic
ReGraph
Tom Sawyer Perspectives
metaphactory
Integrations
AWS App Mesh
AWS Marketplace
Amazon Quantum Ledger Database (QLDB)
G.V() Gremlin IDE
KeyLines
KgBase
New Relic
ReGraph
Tom Sawyer Perspectives
metaphactory
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/neptune/
Vendor Details
Company Name
Maana
Founded
2012
Country
United States
Website
www.maana.io/knowledge-platform/
Product Features
NoSQL Database
Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization