DEX is a high-performance and scalable graph database management system written in Java and C++. One of its main characteristics is its query performance for the retrieval and exploration of large networks. Its implementation with very light specialized structures allows analysing and querying billions of objects at very low storage cost.
Why Dex
Please feel free to DOWNLOAD the evaluation version of DEX
- High-performance for very large networks with billions of objects
- Persistent storage for large volumes of data
- Fast answering time for complex queries
- Relationships between entities implicit in the model
- Allows to have an unified view for multiple sources
- Flexible managing unknown or dynamic schemas
- Graph algorithms to improve the analysis of the connected information in network-like structures
- Rich and versatile APIs
- Diverse graph visualization formats
- Lots of different already explored scenarios where graphs are the key solution
- Easy painless deployment
- Specialized support with fully experienced engineers
- Successful stories to share at national and international level
Why Graph Databases
New solutions for new needs. The emergence of huge networks such as the Internet, geographical systems, transportation or social network databases, has brought the need to manage information with inherent graph-like nature. In these scenarios, users are not only keen on retrieving plain tabular data from entities, but also relationships with other entities using explicit or implicit values and links to obtain more elaborated information. In addition, users are typically not interested in obtaining a list of results, but a set of entities that are satisfying a given constraint. Under these circumstances, the natural way to represent results is by means of graphs. As a consequence, classical database management systems (DBMS), typically based on the relational model, may fall short to answer queries with these objectives.
- Relationships between entities implicit in the model
- More flexible to manage unknown or dynamic schemas
- Structural queries
- Navigational queries
- More efficient to solve network operations
Scenarios for DEX
Where relationships are relevant
- Social Networks ( See more details )
- Twitter, Facebook, Linkedin, Flickr, Delicious, MySpace
- Information Networks
- Bibliographical databases, Wikipedia, IMDB
- Security Networks & fraud detection
- Economic transactions analysis
- Recommendation
- ecommerce
- Media Analysis
- Audiovisual content recommendation
- Physical Netorks
- Logistics, Transport, Electrical, Telecom Networks
- Biological Networks
Technical details
A DEX graph is a Labeled Directed Attributed Multigraph. Labeled because nodes and edges in a graph belong to types. Directed because it supports directed edges as well as undirected. An attributed graph allows a variable list of attributes for each node and edge, where an attribute is a value associated to a name, simplifying the graph structure. A multigraph allows multiple edges between two nodes. This means that two nodes can be connected several times by different edges, even if two edges have the same tail, head and label.
- Language: Java, .NET & C++, with C++ core
- Graph-Model: As explained above, labeled and directed attributed multigraph
- APIs:
- Blueprints interface: Check it at tinkerpop blueprints website
- OS Compatibility (Java API):
- Persistency: Disk
- Transactions: ACID partial supported (Consistency and Isolation)
- License: Dual-licensed
Personal evaluation license (free download available here).
Commercial licenses depending on the size of your database range up to billions of objects - Check the list of features available for each version
For more information, please see Tutorial section