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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

Graph Engine (GE) is a powerful distributed in-memory data processing platform that relies on a strongly-typed RAM storage system paired with a versatile distributed computation engine. This RAM store functions as a high-performance key-value store that is accessible globally across a cluster of machines. By leveraging this RAM store, GE facilitates rapid random data access over extensive distributed datasets. Its ability to perform swift data exploration and execute distributed parallel computations positions GE as an ideal solution for processing large graphs. The engine effectively accommodates both low-latency online query processing and high-throughput offline analytics for graphs containing billions of nodes. Efficient data processing emphasizes the importance of schema, as strongly-typed data models are vital for optimizing storage, accelerating data retrieval, and ensuring clear data semantics. GE excels in the management of billions of runtime objects, regardless of their size, demonstrating remarkable efficiency. Even minor variations in object count can significantly impact performance, underscoring the importance of every byte. Moreover, GE offers rapid memory allocation and reallocation, achieving impressive memory utilization ratios that further enhance its capabilities. This makes GE not only efficient but also an invaluable tool for developers and data scientists working with large-scale data environments.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS App Mesh Yes 
AWS Marketplace Yes 
Amazon Quantum Ledger Database (QLDB) Yes 
G.V() Gremlin IDE Yes 
KeyLines Yes 
KgBase Yes 
MapWeave Yes 
New Relic Yes 
ReGraph Yes 
Tom Sawyer Perspectives Yes 
metaphactory Yes 

Integrations

AWS App Mesh No 
AWS Marketplace No 
Amazon Quantum Ledger Database (QLDB) No 
G.V() Gremlin IDE No 
KeyLines No 
KgBase No 
MapWeave No 
New Relic No 
ReGraph No 
Tom Sawyer Perspectives No 
metaphactory No 

Pricing Details

Custom Pricing based on database storage, location, etc
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/neptune/

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

www.graphengine.io

Product Features

NoSQL Database

Auto-sharding Yes 
Automatic Database Replication Yes 
Data Model Flexibility Yes 
Deployment Flexibility Yes 
Dynamic Schemas Yes 
Integrated Caching Yes 
Multi-Model Yes 
Performance Management Yes 
Security Management Yes 

Product Features

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