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What is PuppyGraph?

PuppyGraph enables users to seamlessly query one or more data sources through an integrated graph model. Unlike traditional graph databases, which can be expensive, require significant setup time, and demand a specialized team for upkeep, PuppyGraph streamlines the process. Many conventional systems can take hours to run multi-hop queries and struggle with managing datasets exceeding 100GB. Utilizing a separate graph database can complicate your architecture due to fragile ETL processes, which can ultimately raise the total cost of ownership (TCO). PuppyGraph, however, allows you to connect to any data source, irrespective of its location, facilitating cross-cloud and cross-region graph analytics without the need for cumbersome ETLs or data duplication. By directly integrating with your data warehouses and lakes, PuppyGraph empowers you to query your data as a graph while eliminating the hassle of building and maintaining extensive ETL pipelines commonly associated with traditional graph configurations. You can say goodbye to the delays in data access and the unreliability of ETL operations. Furthermore, PuppyGraph addresses scalability issues linked to graphs by separating computation from storage, which enhances efficient data management. Overall, this innovative solution not only boosts performance but also simplifies your overall data strategy, making it a valuable asset for any organization.

What is Amazon Neptune?

Amazon Neptune is a powerful and efficient fully managed graph database service that supports the development and operation of applications reliant on complex interconnected datasets. At its foundation is a uniquely crafted, high-performance graph database engine optimized for storing extensive relational data while executing queries with minimal latency. Neptune supports established graph models like Property Graph and the W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which facilitates the effortless crafting of queries that navigate intricate datasets. This service plays a crucial role in numerous graph-based applications, such as recommendation systems, fraud detection, knowledge representation, drug research, and cybersecurity initiatives. Additionally, it equips users with tools to actively identify and analyze IT infrastructure through an extensive security framework. Furthermore, the service provides visualization capabilities for all infrastructure components, which assists in planning, forecasting, and mitigating risks effectively. By leveraging Neptune, organizations can generate graph queries that swiftly identify identity fraud patterns in near-real-time, especially concerning financial transactions and purchases, thereby significantly enhancing their overall security protocols. Ultimately, the adaptability and efficiency of Neptune make it an invaluable resource for businesses seeking to harness the power of graph databases.

Media

Media

Integrations Supported

AWS Deep Learning AMIs
Amazon Redshift
Amazon Web Services (AWS)
Apache Hudi
Apache Parquet
Coinbase
Dremio
Go
Gremlin
IPFS
Java
JavaScript
Linkurious
Microsoft Azure
Microsoft Excel
Upsolver

Integrations Supported

AWS Marketplace
G.V() Gremlin IDE
Tom Sawyer Perspectives

API Availability

API Availability

Pricing Information

Free
Free Version
Free Trial Offered?

Pricing Information

Custom Pricing based on database storage, location, etc

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

PuppyGraph

Company Location

United States

Company Website

www.puppygraph.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/neptune/

Categories and Features

Graph Databases

Not specified

Query Engines

Not specified

Categories and Features

Drug Discovery

Not specified

Graph Databases

Not specified

NoSQL Database

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

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