TITAN Database
Titan is a distributed graph database designed for storing and managing very large graphs.
- Since:2011
- Discord:@TcF9nZu
- Dockerhub:titan
- Docs:http:
- License:github.com
- Official:http:
- Reddit:r/titan
- Repository:github.com
- StackOverflow:[titan]
- Twitter:@thinkaurelius
#What is TITAN?
TITAN Database is a distributed graph database developed by Aurelius. It is built on top of Apache Cassandra and allows for the efficient storage and retrieval of graph-based data. TITAN Database is designed to handle massive datasets and is well-suited for use in large-scale applications.
#TITAN Key Features
Some of the most recognizable features of TITAN Database include:
- Support for a variety of storage backends, including Apache Cassandra, HBase, and Oracle Berkeley DB.
- An extensible data model that supports both property graphs and RDF graphs.
- A distributed architecture that allows for easy scalability.
- The ability to perform complex graph queries using the Apache TinkerPop Gremlin query language.
- Integration with popular data analysis tools such as Apache Spark and Hadoop.
- A robust set of APIs and drivers for integrating with applications written in a variety of programming languages.
#TITAN Use-Cases
Some of the use cases for TITAN Database include:
- Social networking applications that need to store and analyze large amounts of social graph data.
- Recommendation engines that require efficient querying of graph-based data.
- Fraud detection and prevention systems that need to identify patterns and relationships in large datasets.
- Knowledge management systems that store and analyze complex knowledge graphs.
- Identity and access management systems that require efficient storage and retrieval of user profile data.
- Internet of Things (IoT) applications that require real-time analysis of sensor data.
#TITAN Summary
TITAN Database is a distributed graph database designed for large-scale applications. It offers a variety of storage backends, a flexible data model, and integration with popular data analysis tools. It is well-suited for use in social networking, recommendation engines, fraud detection, knowledge management, identity and access management, and IoT applications.