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What is Graph Story?

Organizations opting for a do-it-yourself approach to implement a graph database should expect a preparation period of approximately 2 to 3 months before reaching a production-ready status. On the other hand, utilizing Graph Story’s managed services can enable you to set up your operational database in mere minutes. You can uncover a range of graph use cases while also examining a comparative analysis between self-hosting and managed services. We support deployments within your current infrastructure, whether it is hosted on AWS, Azure, or Google Compute Engine, and we can accommodate any geographical area. If you need VPC peering or specific IP access restrictions, we can swiftly tailor our services to meet those requirements. For those interested in developing a proof of concept, launching a single enterprise graph instance can be accomplished in just a few clicks. If your needs shift towards scaling up to a high-availability production cluster, we are ready to provide support! Our graph database management tools are crafted to enhance your experience, allowing for easy monitoring of CPU, memory, and disk usage. Furthermore, you will have access to crucial configurations, logs, and the ability to back up your database and restore snapshots as needed. This degree of adaptability guarantees that your graph database management meets your operational needs seamlessly. Additionally, our support team is always available to help troubleshoot any issues, ensuring a smooth experience throughout your database management journey.

What is AllegroGraph?

AllegroGraph stands out as a groundbreaking solution that facilitates limitless data integration, employing a proprietary method to consolidate fragmented data and information into an Entity Event Knowledge Graph framework designed for extensive big data analysis. By leveraging its distinctive federated sharding features, AllegroGraph delivers comprehensive insights and supports intricate reasoning over a distributed Knowledge Graph. Additionally, users of AllegroGraph can access an integrated version of Gruff, an intuitive browser-based tool for graph visualization that aids in uncovering and understanding relationships within enterprise Knowledge Graphs. Moreover, Franz's Knowledge Graph Solution not only encompasses advanced technology but also offers services aimed at constructing robust Entity Event Knowledge Graphs, drawing upon top-tier products, tools, expertise, and experience in the field. This comprehensive approach ensures that organizations can effectively harness their data for strategic decision-making and innovation.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Google Compute Engine
Microsoft Azure

Integrations Supported

Apache Solr
Cloudera
Docker
Hackolade
Kubernetes
MongoDB
PoolParty
Swarm

API Availability

Has API

API Availability

Has API

Pricing Information

$299 per month

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
Windows
Mac

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Graph Story

Date Founded

2014

Company Location

United States

Company Website

www.graphstory.com

Company Facts

Organization Name

Franz Inc.

Company Location

San Francisco Bay Area

Company Website

www.franz.com

Categories and Features

Graph Databases

Not specified

Categories and Features

Data Visualization

Not specified

Database

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Virtualization

Distributed Databases

Not specified

Graph Databases

Not specified

Graphing

Not specified

Knowledge Management

Not specified

Machine Learning

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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