Real-time graphfor network observability.

From the creators of Quine,
the open-source streaming graph.

Turn High-Volume Data into High-Value Data

Image showing Quine logo turning high-volume event streams into high-value insights.

Find just the events that matter.

Combine multiple high-volume event streams and detect high-value patterns in real time. Ideal for financial and cyber fraud detection, observability, and ETL pipeline use cases.

 QUINE WHITE PAPER
Quine Streaming Graph scales linearly.

Event processing for the new enterprise-scale.

As more companies adopt event-driven architectures and data volumes increase, the meaning of "enterprise-scale" has evolved. Designed for this new paradigm, thatDot scales to over 1M events/sec running on standard hardware, delivering a compelling formula for cost-effective, high-performance event processing. Read how thatDot scales to 1.1 trillion monthly log events.

Eliminate costly, custom micro services.

In order to make event-driven architectures work today, companies are forced to build costly custom mircro services. thatDot eliminates all those costs and headaches so you can focus on solving business problems.

Supports Kafka, Kinesis, and other streaming sources, as well as traditional batch data sources and makes scaling in production faster, simpler, and much less risky.

Simplify your event-driven architecture with thatDot streaming graph.
Streaming graph for event-driven applications.

Streaming graph for event-driven applications.

thatDot platform is built on Quine, the world’s first streaming graph. It is a transformational platform for modern, event-driven businesses. Quine’s cutting-edge streaming graph technology delivers high-throughput, low-latency pattern detection over complex events without time windows. Available in Community version or as part of thatDot Platform.

thatDot CEO Ryan Wright will be presenting at Knowledge Graph Conference 2023 (May 8 - 13 in NYC).

What is Streaming Graph?

Quine Streaming Graph provides real-time graph ETL on event streams. Quine combines key features of graph databases like Neo4J and event processing platforms like Flink. Turn categorical data from event streams, logs, and data lakes into a single, unified view of your business.

LEARN MORE

Scale beyond traditional
graph databases

Quine scales to millions of events/sec running on standard hardware, delivering a compelling formula for cost-effective, high-performance event processing.

A graph showing Quine sustaining 1 million events/sec.
QUINE ENTERPRISE

Key Integrations include Kafka, Kinesis

Platform Comparison

Open Source Edition

  • Open source streaming graph software.

  • Query unbounded data in real time. No time windows.

  • Ingest multiple data streams.

  • Build real-time data pipelines that trigger automated workflow.

  • 10K+ events/second.

  • Free and open from the Quine Community.

Enterprise

  • For enterprise-scale event stream processing and graph applications.

  • Includes Quine, Novelty Detector, Clustering for resilience and scale.

  • Multi-availability zone deployments.

  • 24x7 Support with SLAs.

  • Scale to 1M+ events/second.

  • Subscriptions and support available from thatDot—the creators of Quine.

What People Are Saying

"The security industry is headed towards leveraging knowledge graphs of all the relevant evidence provided by threat groups, network indicators and endpoint artifacts to quickly identify and mitigate threats. The security companies that can most confidently extract relevant context from these graph and then immediately action on findings to mitigate threats will be the winners. This is exactly the problem Quine aims to address.”

Evan Wright
Staff Data Scientist, Mandiant

“thatDot Platform's advanced Novelty Scoring for categorical data feature is the future of anomaly detection. Its speed powers our new real-time services while also significantly reducing false-positive findings for our customers.”

Gery Szlobodnyik
CEO, TraceRiser

We use cookies to ensure you
get the best experience on our website. Learn More

Got it