Uses for individual data engineering technologies are often broadened to more than just interacting with databases. The same goes for graph database techniques and, specifically, the leading language for building and querying graph databases – Cypher.
Watch Quine in action. Learn about graph ETL uses cases from three recent live demos.
Learn how Quine achieves groundbreaking performance for real-time complex event processing and how you can reproduce the results.
Real-time video observability presents a number of data engineering challenges that graph ETL can solve.
Learn how easy it is to use Quine streaming graph’s idFrom function to deduplicate Kafka (or any other) event streams.
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.
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.
This blog shows you how Quine streaming graph can ingest multiple log formats to create a single, unified streaming graph for real-time analysis.
Ingest multiple data sources into Quine in order create a single streaming graph. ETL basics and Cypher queries are covered.
A step-by-step guide to ingesting data into Quine from live internet streams. ETL basics and Cypher queries are covered.
Part one in a series connecting different data producers to Quine streaming graph. Use Cypher to create ingest queries (ETL).
Matthew Splett from Tripwire explains how he replaced complex SQL queries with succinct Cypher queries to process rollup data.
We introduced the term “3D Data” as a mnemonic and a way to think about streaming data processing that incrementally builds toward human-level data questions.