The thatDot team had a great time last week at Confluent’s big conference, Current 2024. We talked to a lot of folks about the power of Streaming Graph, an event stream processor with a graph data model.
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 are particularly well-suited for scenarios where relationships and patterns are important, but until recently, they have been confined to a handful of use cases – databases, chip design, information theory, AI – that all have one thing in common: the data in question is stored first and then processed, usually as a batch...
This lightning talk will highlight two approaches to real-time entity resolution on streaming data using the Quine streaming graph.
Briefing Room on demand webinar on thatDot Youtube channel: The Unreasonable Effectiveness of Streaming Graph thatDot founder and CEO Ryan Wright discussed the power of thatDot Streaming Graph and Novelty to detect the most well-hidden threats with the Bloor Group's Eric Kavenagh and Mark Lynd, who was ranked #1 global thought leader in cybersecurity by Thinkers360. With high-profile data breaches hitting the headlines every other day now, the way we're doing this is clearly a losing battle....
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 prioritizes risk minimization, their methods for calculating risk often rely on detailed analysis of categorical data and relationships. Most existing algorithms, however, only handle static, numeric data. This requires transforming the data, typically through methods like one-hot encoding, into numerical formats that...
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.
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.
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.
At the 2023 Knowledge Graph Conference in New York, Ryan Wright, CEO and Founder of thatDot, gave a presentation entitled: Streaming Graphs: Because We Cannot Afford to Query Anymore. Quine streaming graph can process millions of complex, multi-hop graph events per second. But what design decisions and tradeoffs went into making this possible? And why does it matter to data engineers and their day-to-day? Learn how Quine integrates with your event streaming pipeline (including Apache Kafka,...
On RTInsights, thatDot's Rob Malnati writes about digital twins. This article provides a solid foundation as to what digital twins are, what they're used for, and how streaming graph technology can make them more effective. "As our world becomes increasingly connected, digital twins abstract and model almost everything to improve business operations, reduce risk, and enhance decision-making for better outcomes." "For digital twins to be truly useful, they must be able to drive actions – for...
Streaming Graph Analytics, and what it does. In this article on Venturebeat, George Anadiotis discusses the power of Quine, the increasing interest in the concept of streaming graph, and the influx of thatDot funding from cybersecurity leader Crowdstrike. "What do you get when you combine two of the most up-and-coming paradigms in data processing — streaming and graphs? Likely a potential game-changer, at least that’s what is being hinted at by the likes of DARPA and now...
In this article on Datanami, Alex Woodie discusses the problems with current event stream processing data pipelines, and the advantages a graph paradigm could bring to the table, with thatDot technology spotlighted. He talks about how thatDot's Ryan Wright found himself having to rebuild the data pipeline infrastructure of multiple times, and how brittle and difficult to maintain it could be. “The more data pipelines you build, the more they start looking like the same thing,” Wright says....
On InfoQ, Sergio De Simone talks about the advantages of the streaming graph style of data processing, and of Quine open source software in particular. "What sets Quine apart from other stream processing solutions, says thatDot, is a set of three design choices that lie at its foundations: a graph-structured data model, an asynchronous actor-based graph computational model, and standing queries." Check out "Quine Aims to Simplify Event Processing on Data in Motion" on InfoQ to learn...
On TechCrunch.com, Frederic Lardinois talks about the launch of Quine open source streaming graph complex event processing engine. “We’ve developed the streaming graph to really target the kind of the problem in the industry right now — the rock and hard place that we all sit between,” Quine’s creator and thatDot CEO and co-founder Ryan Wright told me. “On one side, there’s huge volumes of data. For the last 10 years, big data has just become de rigueur, it’s a normal ordinary thing...
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 Leader, Mark Lynd, as they discuss "The Unreasonable Effectiveness of Streaming Graph." This insightful discussion is a must-attend for anyone serious about cybersecurity, threat detection, and deep, real-time analytics. Event Details: Title: The Unreasonable Effectiveness of Streaming Graph Date: June 11, 2024 Time: 12...
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).
Add some flair to your Quine streaming graph visualizations while learning about the API at the same time.
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.
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 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.
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 release includes improvements for scalability, stability, and supernode mitigation plus work key to reaching 1M events/sec.
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.
Stream processing offers the opportunity to detect important patterns in information and act in real time.
Learn how easy it is to use Quine streaming graph’s idFrom function to deduplicate Kafka (or any other) event streams.
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.
Standing queries let you embed business logic in your real-time graph analytics workstream.
Quine 1.3.0 is out and includes features, recipes, and documentation all aimed at improved streaming graph usability.
Quine is a natural fit for Kafka data pipelines. Consume data from Kafka topics, publish processed data to Kafka topics.
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.