Streaming Graph Get Started
It's been said that graphs are everywhere. Graph-based data models provide a flexible and intuitive way to represent complex relationships and interconnectedness in data. They a...
Posts by thatDot
Streaming Graph for Real-Time Risk Analysis at Data Connect in Columbus 2024
After more than 25 years in the data management and analysis industry, I had a brand new experience. I attended a technical conference. No, that wasn’t the new thing. At many co...
The Power of Real-Time Entity Resolution with Ryan Wright
This lightning talk will highlight two approaches to real-time entity resolution on streaming data using the Quine streaming graph.
Cypher all the things!
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.
Streaming Graph Processing on Categorical Data Enables Real-time Risk Calculation
The failure of Silicon Valley Bank in 2023 exemplifies the severe consequences of not accurately assessing risk in a timely manner. Although nearly every financial institution p...
Akka to Pekko Migration for thatDot and Quine
Discover how thatDot's migration to Pekko from Akka not only ensured functionality and community support but also reduced maintenance burden, avoided extra expenses for SAAS products, and provided access to new libraries and community releases.
Microservice Hell: The State of the Art in Streaming Services
Exploring the challenges of data processing in microservices, the article introduces thatDot's Streaming Graph, which seamlessly integrates various data sources like Apache Kafka, AWS Kinesis, and more.
Novelty Demo
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Release Announcement for thatDot Streaming Graph 1.6.1 with ClickHouse Persistor
View the latest release of thatDot Streaming Graph (v1.6.1), highlighting new features such as data persistence in ClickHouse, namespace management, robust Kafka integration, simplified queries, and error fixes related to Cypher query compilation.
Authentication Fraud
Metered attacks that generate low volume log-in attempts, from diverse IPs and across extended time frames, are designed to avoid the "3 strikes in 24 hours" business rules in a...
Financial Fraud Detection
Financial fraud detection requires monitoring billions of transactions, devices and users in real-time for suspect behaviors without false positives that alienate customers when...
Graph AI
Pick One.
Log Analysis
Monitoring systems comprised of multiple services is typically done by monitoring each service individually using it's logs, or on an end to end basis that lacks visibility into...
Real-time Blockchain Fraud Detection
Real-time linking of transactions, accounts, wallets, and blocks within and across blockchains is not possible with current solutions. Instead, the user must either rely on batc...
Stateful Digital Twin
While digital twins and the emerging subcategory of asset graphs promise operators greater visibility into the relationships between IT assets and equipment under management, cu...
Streaming Graph ETL
Most ETL tools use the batch processing paradigm to find high-value patterns in large volumes of data. Whether the specific business application is fraud detection, cyber securi...
Video Observability for Root Cause Analysis
Real-time video observability that can solve Quality of Experience (QoE) issues while live broadcast events are still playing require the simultaneous monitoring of millions of ...
Novelty Technology
Anomaly detection is a technique for finding important data. Decades of research has been spent on creating tools for anomaly detection with numeric data. But most data produced...
Advanced Persistent Threat (APT) Detection
Discovering advanced persistent threats (APT) is, by design, akin to finding a needle in a haystack.
Real-Time IoB Threat Hunting
Modern threat detection requires data – lots of data – typically from multiple sources. This brings with it a number of interesting data engineering challenges, especially when ...
Real-time AWS CloudTrail Threat Detection
AWS CloudTrail logs are full of untapped information that can help reduce risk and improve event response times, especially when analyzed in context and in real time. A thatDot ...
Webinar: Approach Zero False Positive Cyber Alerts
We would like to invite you to an exclusive webinar featuring thatDot’s CEO, Ryan Wright, and The Bloor Group CEO, Eric Kavanagh, along with Top 5 Global Cybersecurity Thought L...
4 Advantages to Streaming Analytics in Graph Form
Explore the transformative benefits of streaming analytics in graph form, including real-time insights, deep relationship analysis, immediate categorical data processing, and drastically reduced mean time to value (MTTV).
The Future of Modern Threat Hunting is Streaming Graph
Standards-based threat detection & automated response using Quine streaming graph.
Monitoring Quine Streaming Graph using Grafana + InfluxDB
Monitoring tools like Grafana work well with Quine but there are a few things to keep in mind when monitoring data in motion.
Calculate Risk and Optimize Asset Allocation in Real Time
Asset allocation and risk calculations need to move from batch to real time to free assets and improve compliance. Quine Streaming Graph provides a path.
Create a Quine Icon Library with Python
Add some flair to your Quine streaming graph visualizations while learning about the API at the same time.
Dynamic Duo: Quine & Novelty Detector for Insider Threats
In a big update to the VAST Advanced Persistent Threat blog, we demonstrate an end-to-end Quine plus Novelty Detector workflow.
idFrom(): the simple function that’s key to Quine streaming graph
idFrom() seems like a simple function for generating node IDs but it is the key to Quine's ability to find complex patterns in high volume event streams.
Using Indicators of Behavior (IoB) Analysis for IoT data
Indicator of Behavior (IoB) analysis is extending beyond the cybersecurity domain to offer new value for finance, ecommerce, and especially IoT use cases.
Quine’s Real-time Temporal Event Sequencing Produces New Insights
Quine's standing queries, idFrom + deterministic labelling can be use to efficiently create any subgraph you need (e.g. sequence based) in real time. This makes alerts more timely and root cause analysis more efficient.
Graph Neural Networks for Quine
Quine 1.5 includes support for graph neural network techniques like Node2Vec and GraphSAGE. This post provides an overview and tutorial.
Categorical Data: An Untapped Source of Real-Time Insights
Categorical data is an oft-ignored source of valuable business intelligence. Quine makes it easy to process categorical data with your existing ETL pipeline.
Quine Streaming Graph: A Year in Open Source
thatDot's iteratively improving the developer experience: who is Streaming Graph built for, what jobs do they tell us they need to get done.
Quine 1.4.0: Scale, Stability, Supernode Mitigation
Quine 1.4.0 release includes improvements for scalability, stability, and supernode mitigation plus work key to reaching 1M events/sec.
Why Digital Twins Need to Go Real Time
For digital twins to be truly useful in business operations, they must be able to drive actions and do so the instant an issue emerges, perhaps even beforehand.
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.
Quine Streaming Graph 1.3.0: Focus on Usability, Query Performance
Quine 1.3.0 is out and includes features, recipes, and documentation all aimed at improved streaming graph usability.
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.
thatDot, makers of Quine, Announces CrowdStrike Falcon Fund Investment
With the strategic investment from CrowdStrike, thatDot plans to accelerate development of Quine streaming graph and accelerate community adoption.
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.
9 Events, 90 Days - See Quine Streaming Graph in Action
A list of upcoming events plus links to videos of recent presentations, all introducing Quine streaming graph concepts.
Key Concepts to Help You Get Started With Streaming Graph
Advice and key concepts about Quine streaming graph that will accelerate your development.
The Evolution To Streaming Graph from Graph Databases
When it comes to event-driven applications, graph database users require a new approach: streaming graph.
Let's Talk Streaming Graph! (with demo)
Ryan Wright (CEO of thatDot) joins Joe Reis and Matt Housley on the TGIF! Let's Talk Data live show to chat about streaming graphs.
Recipe for Streaming Graph Success
Quine Recipes make it dead easy to connect to your real-time event streams and turn them into stateful streaming graphs
Computing Recursive Rollups in a Kafka Event Streaming Pipeline
Matthew Splett from Tripwire explains how he replaced complex SQL queries with succinct Cypher queries to process rollup data.
Announcing Open Source Release of Quine Streaming Graph
thatDot Releases First Open Source Software to Combine Complex Event Streaming and Graph Data Technologies for Data Pipeline Engineers
AWS Names thatDot's Novelty Detector As A Containers Anywhere Partner
Bringing cloud-based data management into the enterprise data center, where much enterprise data still lives, is now simpler than ever.
Stop Insider Threats With Automated Behavioral Anomaly Detection
Advanced: Finding a malicious employee is one of the toughest cyber-security challenges in the industry.
Quine Streaming Graph Scales to 1.1 Trillion Log Events per Month
Learn how Quine streaming graph achieved a sustained rate of recording 425,000 records per second into our streaming graph.
Data Exfiltration Detection in AWS CloudTrail Logs Using Categorical Data
This blog on AWS data exfiltration detection explains the use of categorical data in anomaly detection to identify multi-stage exploit campaigns in AWS CloudTrail logs.
The Known Security Challenge of the Unknown
Destructive attack campaigns succeed because they integrate new techniques or new hardcoded credentials to access and victimize their targets.
Find Stolen Credentials Use in AWS CloudTrail Logs using Quine Graph
The move to the cloud represents new challenges for enterprise security teams. Use thatDot Novelty Detector to detect the attack quickly.
What Is Categorical Data? Comparing it to Numerical Data for Analytics
Data comes in two flavors: Numeric and Categorical. Numeric data is easy, it’s numbers. Categorical data is everything else.
New to Quine's Novelty Detector: Visualizations and Enhancements
thatDot’s real-time Novelty Detector for categorical has updated its data exploration and data transformation capabilities.
The World’s First Real-time Novelty Detector For Categorical Data
thatDot is excited to share the general availability of the world’s first system for real-time categorical anomaly detection.
Draw Connections to Build Insights
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.
The Three D’s of Graph Data
Draw Connections, Define Data, Drill Down
Defining Video Observability
Imagine if the next time your video streaming operations dashboard-of-choice warns you that 100 users experienced video start failures in the last minute,
Introducing thatDot
That word… ”that.” It’s how you point with a word. What better way to express what you mean than by directly pointing?
thatDot Raises Funding To End Microservices Complexity
thatDot, announces a $2M funding round led by Oregon Venture Fund (OVF), with participation by Hale Capital Partners and Galois, Inc.