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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 HugeGraph?

HugeGraph is a highly efficient and scalable graph database designed to handle billions of vertices and edges with impressive performance, thanks to its strong OLTP functionality. This database facilitates effortless storage and querying, making it ideal for managing intricate data relationships. Built on the Apache TinkerPop 3 framework, it enables users to perform advanced graph queries using Gremlin, a powerful graph traversal language. A standout feature is its Schema Metadata Management, which includes VertexLabel, EdgeLabel, PropertyKey, and IndexLabel, granting users extensive control over graph configurations. Additionally, it offers Multi-type Indexes that support precise queries, range queries, and complex conditional queries, further enhancing its querying capabilities. The platform is equipped with a Plug-in Backend Store Driver Framework, currently compatible with various databases such as RocksDB, Cassandra, ScyllaDB, HBase, and MySQL, while also providing the flexibility to integrate further backend drivers as needed. Furthermore, HugeGraph seamlessly connects with Hadoop and Spark, augmenting its data processing prowess. By leveraging Titan's storage architecture and DataStax's schema definitions, HugeGraph establishes a robust framework for effective graph database management. This rich array of features solidifies HugeGraph’s position as a dynamic and effective solution for tackling complex graph data challenges, making it a go-to choice for developers and data architects alike.

Media

Media

Integrations Supported

AWS Deep Learning AMIs
Amazon EC2
Amazon Redshift
Amazon Web Services (AWS)
Apache Iceberg
Apache Parquet
Coinbase
Datadog
Delta Lake
Docker
Dremio
Go
Google Cloud Platform
Java
Microsoft Azure
Microsoft Excel
SingleStore
Snowflake

Integrations Supported

Hadoop
Spark

API Availability

API Availability

Has API

Pricing Information

Free
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

PuppyGraph

Company Location

United States

Company Website

www.puppygraph.com

Company Facts

Organization Name

HugeGraph

Date Founded

2018

Company Website

github.com/hugegraph/hugegraph

Categories and Features

Graph Databases

Not specified

Query Engines

Not specified

Categories and Features

Graph Databases

Not specified

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