Drive Streaming Event Workflows with Standing Queries
Standing queries let you embed business logic in your real-time graph analytics workstream.
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thatDot is transforming cybersecurity with innovative Streaming Graph technology. By merging real-time event stream processing with powerful graph analytics, thatDot offers unparalleled capabilities in threat detection and response, ensuring robust protection against modern cyber threats.
Understanding the Scale Limitations of Graph Databases
As graph database adoption accelerates, new data infrastructures like streaming graph will emerge to eliminate the scale struggles of graph databases.
Network Log Analysis Using Categorical Anomaly Detection
The distributed nature of modern virtualized software architectures has created added complexity in the networking stack, making it difficult to attribute behavior to any single service.
Reducing False Positive Alerts With Contextual Anomaly Detection
Traditionally, monitoring alerts are produced comparing metrics against thresholds to identify behavior outside the norm.
Where Quine Streaming Graph Fits In Kafka-Based Data Pipelines
Quine is a natural fit for Kafka data pipelines. Consume data from Kafka topics, publish processed data to Kafka topics.
Ingest How-To: Real-time Graph Analytics for Kafka Streams with Quine
Blog #5 in the Ingesting Data series. A step-by-step guide to adding Quine's high-volume graph analytics inline with your Kafka-based event streams.
Modernizing ETL For Cloud
Cloud architectures enable a new level of integration with 3rd party systems and data sources to deliver the services our users and customers are looking for.
Ingest and Analyze Log Files Using Streaming Graph
This blog shows you how Quine streaming graph can ingest multiple log formats to create a single, unified streaming graph for real-time analysis.