TigerGraph
Graph database for real-time AI and analytics
TigerGraph is a distributed native graph database and graph AI platform that stores data as entities and their relationships, enabling multi-hop queries and analytics across connected datasets. It addresses the limitations of traditional databases in finding deep, multi-dimensional relationships, supporting use cases such as fraud detection, anti-money laundering, customer intelligence, supply chain analysis, and digital twins.
Core capabilities include the GSQL query language, GraphStudio visual SDK, Graph Data Science Algorithm Library, Insights no-code visualization add-on, Solution Kits, ML Workbench for graph-based machine learning, and a GraphQL Service. Built-in connectors support Kafka, cloud object stores (Amazon S3, Azure Blob Storage, Google Cloud Storage), Snowflake, Google BigQuery, PostgreSQL, Spark-based platforms, and JDBC. Deployment runs on Kubernetes across AWS, Azure, GCP, and on-premise environments, with ACID compliance, fine-grained security, policy enforcement, and provenance tracking.
TigerGraph is aimed at data scientists, developers, and enterprises in regulated industries such as financial services, manufacturing, retail, and telecom. Products include TigerGraph Enterprise for self-managed on-premises deployment and TigerGraph Savanna, a cloud-based graph database-as-a-service available on multiple cloud platforms with AI/ML add-ons. A free trial is offered.
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