Blog
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.
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.
Ingesting From Multiple Data Sources into Quine Streaming Graph
Ingest multiple data sources into Quine in order create a single streaming graph. ETL basics and Cypher queries are covered.
Real-time Blockchain Monitoring is Hard without A Streaming Graph
As crypto currencies go mainstream, better techniques for protecting users from fraud are needed. Enter streaming graph.
Ingesting data from the internet into Quine Streaming Graph
A step-by-step guide to ingesting data into Quine from live internet streams. ETL basics and Cypher queries are covered.
Building a Quine Streaming Graph: Ingest Streams
Part one in a series connecting different data producers to Quine streaming graph. Use Cypher to create ingest queries (ETL).
Time Series Streaming Graph and other Quine 1.2.0 Highlights
Quine 1.2.0 release sees significant new features, recipes, and performance enhancements.
Your Graph DB Won’t Scale? Stop Querying it.
Stop approaching streaming data the same way you do persistent data. Teach the stream to tell you when something interesting happens.
Key Concepts to Help You Get Started With Streaming Graph
Advice and key concepts about Quine streaming graph that will accelerate your development.