What is the difference between batch and stream processing?
Stream processing offers the opportunity to detect important patterns in information and act in real time.
See Quine in Action: 3 Live Demos Showing Graph ETL Use Cases
Watch Quine in action. Learn about graph ETL uses cases from three recent live demos.
Great Quine Community Events for October 2022
Upcoming Community Events – Workshops, Developer Days, and Conferences in October 2022
Scaling Quine Streaming Graph to Process 1 Million Events/Second
Learn how Quine achieves groundbreaking performance for real-time complex event processing and how you can reproduce the results.
Streaming Graph ETL: Real-time Video Observability Simplified
Real-time video observability presents a number of data engineering challenges that graph ETL can solve.
Are You Ready for Low and Slow Auth Attacks?
Quine streaming graph detects hard to find password spraying attacks for IAM providers and enterprises alike.
What’s the difference between Categorical and Numerical Data?
Categorical data is enormously useful but often discarded because, unlike numerical data, there were few tools available to work with it until graph DBs and streaming graph came along.
Kafka data deduping made easy using Quine’s idFrom function
Learn how easy it is to use Quine streaming graph’s idFrom function to deduplicate Kafka (or any other) event streams.
Save Big on SIEM Storage Costs Using Quine’s Semantic ETL
Quine reduces Splunk and New Relic costs by evaluating data as it arrives and making choices to store or discard based on the value of the data.
Drive Streaming Event Workflows with Standing Queries
Standing queries let you embed business logic in your real-time graph analytics workstream.