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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 Cayley?

Cayley is an open-source database specifically designed for Linked Data, inspired by the graph database that underpins Google's Knowledge Graph, which was formerly known as Freebase. This database prioritizes user-friendly design while effectively managing complex data structures; it includes a built-in query editor, visualizer, and Read-Eval-Print Loop (REPL) functionality. It supports a variety of query languages, such as Gizmo, which is modeled after Gremlin, a query language similar to GraphQL, along with MQL, a simplified version aimed at Freebase users. With its modular architecture, Cayley seamlessly integrates with preferred programming languages and backend storage solutions, making it production-ready and well-tested, with numerous companies relying on it for their operational needs. Furthermore, its optimization for application use showcases remarkable performance; for example, it has been demonstrated to handle 134 million quads in LevelDB on standard 2014 hardware, with multi-hop intersection queries—like identifying films featuring both X and Y—executing in around 150 milliseconds. By default, Cayley operates in-memory, reflecting the capabilities of its backend memstore, which significantly boosts its speed and efficiency during data retrieval and manipulation. Overall, Cayley stands as a robust solution for developers aiming to harness linked data in their applications, while its continuous improvements and community support ensure it keeps pace with evolving technological demands.

Media

Media

Integrations Supported

Docker
Alchemy Pay
Apache Hudi
Apache Parquet
CFN Insight
Databricks
Datadog
Dremio
Google Sheets
Java
JavaScript
Linkurious
Microsoft Azure
Microsoft Excel
PostgreSQL
SQL
Upsolver

Integrations Supported

Docker
GraphQL
KeyLines

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
Mac
Linux

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

Cayley

Company Website

github.com/cayleygraph/cayley

Categories and Features

Graph Databases

Not specified

Query Engines

Not specified

Categories and Features

Graph Databases

Not specified

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