TigerGraph Version 3 (Enterprise Edition)
TigerGraph
Price: Typical Total Price$2.356/hrTotal pricing per instance for services hosted on r4.xlarge in US East (N. Virginia). View Details
Product Overview
TigerGraph is an analytics platform for creating big graph applications -- opening up new possibilities for graph technology. TigerGraph offers a native enterprise MPP (massively parallel processing) database and GraphStudio, a visual SDK to easily design and explore your graph. TigerGraph supports applications such as AI and machine learning and real-time analytics for IoT, Customer 360, recommendation, anti-fraud, temporal and geospatial analysis, and cybersecurity, to make sense of ever-changing big data. The Enterprise Edition includes multi user Role-Based Access Control and MultiGraph(TM), for managing multiple data domains with secure sharing. The hourly paid VM image is designed for single instance use. If you are ready to run a TigerGraph cluster on AWS, please contact TigerGraph Sales for custom pricing: [email protected]
Version: 3.9.3-3
By: TigerGraph
Categories: Databases
Data Analytics
ML Solutions
Operating System
Linux/Unix, Amazon Linux Amazon Linux 2 AMI
Delivery Methods
Amazon Machine Image
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Highlights: Continuously load over 100 GB per machine per hour. Write high-performance complex analytics queries using GSQL, the Turing-complete, easy-to-use, SQL-like graph query language with built-in parallelism. Perform graph traversals of 3 to 10+ hops with subsecond results, across massive graphs with trillions of vertices and edges, to support complex queries.
Category: Infrastructure Software
Delivery Method: Amazon Machine Image
Company Information
Company Name: TigerGraph
About Company: TigerGraph is the world's fastest graph analytics platform powered by Native Parallel Graph (NPG) technology. TigerGraph fulfills the true promise and benefits of the graph platform by tackling the toughest data challenges in real time, no matter how large or complex the dataset. TigerGraph supports applications such as IoT, AI and machine learning to make sense of ever-changing big data.