About
Apache TinkerPop™ is a graph computing framework for both graph databases (OLTP) and graph analytic systems (OLAP). Gremlin is the graph traversal language of Apache TinkerPop. Gremlin is a functional, data-flow language that enables users to succinctly express complex traversals on (or queries of) their application's property graph. Every Gremlin traversal is composed of a sequence of (potentially nested) steps. A graph is a structure composed of vertices and edges. Both vertices and edges can have an arbitrary number of key/value pairs called properties. Vertices denote discrete objects such as a person, a place, or an event. Edges denote relationships between vertices. For instance, a person may know another person, have been involved in an event, and/or have recently been at a particular place. If a user's domain is composed of a heterogeneous set of objects (vertices) that can be related to one another in a multitude of ways (edges).
|
About
GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use.
|
About
The JavaScript InfoVis Toolkit provides tools for creating interactive data visualizations for the web. The best way to start is to take a look at the demos page. Each demo has a See the Example Code link that takes you to the code for that example. The actual library code is included in the HTML file by building the lib each time with only the needed requirements taken from the name of the visualization and the build.json file. The required library code is built by the build.py file. In order to create a new visualization you need to set up the server environment to include test JavaScript files for your new visualization and also you need to add the new visualization files into the Source folder.
|
About
RelationalAI is a next-generation database system for intelligent data applications based on relational knowledge graphs. Data-centric application design brings data and logic together into composable models. Intelligent data applications understand and make use of each relation that exists in a model. relational provides a knowledge graph system to express knowledge as executable models. These models can be easily extended through declarative, human-readable programs. RelationalAI’s expressive, declarative language leads to a 10-100x reduction in code. Applications are developed faster, with superior quality by bringing non-technical domain experts into the creation process and by automating away complex programming tasks. Take advantage of the extensible graph data model as the foundation of data-centric architecture. Integrate models to discover new relationships and break down barriers between applications.
|
|||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||
Audience
Developers seeking a solution to manage their graph databases and graph analytic systems
|
Audience
Companies and developers interested in a graph database management system solution optimize the creation and maintenance of complex data graphs
|
Audience
Developers in need of a tool for creating interactive data visualizations for the web
|
Audience
Professional users seeking a solution to improve their relational knowledge graph management system
|
|||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||
API
Offers API
|
API
Offers API
|
API
Offers API
|
API
Offers API
|
|||
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
|||
Pricing
Free
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
Pricing
Free
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||
Reviews/
|
Reviews/
|
Reviews/
|
Reviews/
|
|||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||
Company InformationApache Software Foundation
United States
tinkerpop.apache.org
|
Company InformationFactNexus
Founded: 2010
Australia
graphbase.ai/
|
Company InformationSenchaLabs
Founded: 2013
United States
philogb.github.io/jit/
|
Company InformationRelationalAI
United States
relational.ai/
|
|||
Alternatives |
Alternatives |
Alternatives |
Alternatives |
|||
|
|
|
|||||
|
|
|
|
||||
|
|
|
|||||
|
|
|
|||||
Categories |
Categories |
Categories |
Categories |
|||
Integrations
Apache Groovy
Docker
G.V() - Gremlin IDE
Java
Node.js
Python
Wink
|
Integrations
Apache Groovy
Docker
G.V() - Gremlin IDE
Java
Node.js
Python
Wink
|
Integrations
Apache Groovy
Docker
G.V() - Gremlin IDE
Java
Node.js
Python
Wink
|
Integrations
Apache Groovy
Docker
G.V() - Gremlin IDE
Java
Node.js
Python
Wink
|
|||
|
|
|
|
|