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
Apache TinkerPop™ serves as a framework for graph computing, catering to both online transaction processing (OLTP) with graph databases and online analytical processing (OLAP) through graph analytic systems. The traversal language utilized within Apache TinkerPop is known as Gremlin, which is a functional, data-flow language designed to allow users to effectively articulate intricate traversals or queries related to their application's property graph. Each traversal in Gremlin consists of a series of steps that can be nested. In graph theory, a graph is defined as a collection of vertices and edges. Both these components can possess multiple key/value pairs referred to as properties. Vertices represent distinct entities, which may include individuals, locations, or events, while edges signify the connections among these vertices. For example, one individual might have connections to another, have participated in a certain event, or have been at a specific location recently. This framework is particularly useful when a user's domain encompasses a diverse array of objects that can be interconnected in various ways. Moreover, the versatility of Gremlin enhances the ability to navigate complex relationships within the graph structure seamlessly.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Docker
Yes
Apache Groovy
No
Apache Solr
Yes
Cloudera
Yes
G.V() Gremlin IDE
No
Hackolade
Yes
Java
No
Kubernetes
Yes
MongoDB
Yes
Node.js
No
Integrations
Docker
Yes
Apache Groovy
Yes
Apache Solr
No
Cloudera
No
G.V() Gremlin IDE
Yes
Hackolade
No
Java
Yes
Kubernetes
No
MongoDB
No
Node.js
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
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
Apache Software Foundation
Country
United States
Website
tinkerpop.apache.org
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