TigerGraph is a platform for advanced analytics and machine learning on connected data, based on the industry’s first and only distributed native graph database. A graph database is a data management system software in which the building blocks are vertices and edges. Graph databases excel at answering complex questions about relationships in large data sets. However, when the volume of data grows very large, they hit a wall. As existing graph technologies have trouble load large quantities of data or ingesting fast arriving data in real time. They slow down or time out after two hops of traversal. On the other hand, TigerGraph, being a distributed, native graph computing platform, gets around these limitations making it an exciting piece of technology for companies to keep in their arsenal.
- Provides deep link analytics in real-time.
- Designed with intuitive features, TigerGraph’s comprehensive graph platform empowers data scientists and developers to deliver innovative graph solutions. These are based on algorithms such as PageRank and Community Detection in hours. From GSQL, intuitive SQL-like graph query language to visual Graph Studio SDK.
- Supports advanced analytics and machine learning applications. These include fraud detection, anti-money laundering (AML), entity resolution, customer 360, recommendations, knowledge graph, cybersecurity, supply chain, IoT, and network analysis.
- All data loaded into TigerGraph Cloud, including data in disk storage and backups, are automatically encrypted-at-rest. It uses the cloud provider’s native encryption protocol with platform-managed keys.
- TigerGraph Cloud uses TLS to encrypt connections to your graph databases.