Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AllegroGraph represents a revolutionary advancement that facilitates limitless data integration through a proprietary methodology that merges all types of data and isolated knowledge into a cohesive Entity-Event Knowledge Graph, which is capable of handling extensive big data analytics. It employs distinctive federated sharding features that promote comprehensive insights and allow for intricate reasoning across a decentralized Knowledge Graph. Additionally, AllegroGraph offers an integrated version of Gruff, an innovative browser-based tool designed for visualizing graphs, helping users to explore and uncover relationships within their enterprise Knowledge Graphs. Furthermore, Franz's Knowledge Graph Solution encompasses both cutting-edge technology and expert services aimed at constructing robust Entity-Event Knowledge Graphs, leveraging top-tier tools, products, and extensive expertise to ensure optimal performance. This comprehensive approach not only enhances data utility but also empowers organizations to derive deeper insights and drive informed decision-making.
Description
A worldwide device knowledge graph delivers organized and comprehensive insights regarding electronic devices, their functionalities, and the services they provide, along with the interconnections among them. Each device found in a household possesses an array of properties, including its brand, model, series number, manufacturer, present features and services, both physical and software attributes, compatible devices, regional data, and much more. This vast assortment of information about nearly every audiovisual device globally is housed within QuickSet’s device knowledge graph. QuickSet utilizes this knowledge graph to offer an extensive suite of functionalities for any given device. In addition to basic control, this knowledge graph infuses essential context into all user commands and actions, facilitating the dynamic identification of nearby devices. The algorithms employed by QuickSet depend on the knowledge graph that encompasses devices with diverse control capabilities, communication interfaces, and protocols, ensuring seamless interaction among devices. Ultimately, this interconnected system enhances user experience by making device management more intuitive and efficient.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Apache Solr
Yes
Cloudera
Yes
Docker
Yes
Hackolade
Yes
Kubernetes
Yes
MongoDB
Yes
PoolParty
Yes
Swarm
Yes
Integrations
Apache Solr
No
Cloudera
No
Docker
No
Hackolade
No
Kubernetes
No
MongoDB
No
PoolParty
No
Swarm
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
Yes
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
Yes
Mac
Yes
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
Franz Inc.
Country
San Francisco Bay Area
Website
www.franz.com
Vendor Details
Company Name
QuickSet Cloud
Country
United States
Website
quicksetcloud.com/device-knowledge-graph/
Product Features
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
Database
Backup and Recovery
Yes
Creation / Development
Yes
Data Migration
Yes
Data Replication
Yes
Data Search
Yes
Data Security
Yes
Database Conversion
Yes
Mobile Access
Yes
Monitoring
Yes
NOSQL
Yes
Performance Analysis
Yes
Queries
Yes
Relational Interface
No
Virtualization
Yes
Knowledge Management
Artificial Intelligence (AI)
No
Cataloging / Categorization
No
Collaboration
No
Content Management
No
Decision Tree
No
Discussion Boards
No
Full Text Search
No
Knowledge Base Management
No
Self Service Portal
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
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