Apache Flink & Ververica Platform Use Cases

Hyperconnect, the creators of matchmaking app Azar, built a distributed, streaming architecture for Azar's Matchmaking service that performs real-time machine learning, powered by Apache Flink.

Humn.ai uses Ververica Platform and Apache Flink to build a Machine Learning-based platform producing dynamic risk assessment models and real-time pricing for tomorrow’s insurance industry.

Weibo uses Apache Flink to develop real-time Machine Learning pipelines and perform multi-stream joins at scale.

GoDaddy's developed a streaming data platform and chose Apache Flink as the underlying streaming engine for the company's streaming data pipelines.

Salesforce uses Apache Flink for intelligent log analysis and performance engineering insights at large scale.

FLOW is an abstraction layer on top of Flink allowing teams at SK telecom to submit their data using SQL, and build streaming pipelines with Apache Flink.

Bird uses Flink to detect when scooters go offline using Apache Flink's event time, watermarks, and ordering.

The team at Pinterest developed a real-time experimentation platform for running experiment analytics using Apache Flink.

The User Location Intelligence team at Yelp leverages Apache Flink for online Machine Learning models, predicting real-time store visits at scale.

Klaviyo leverages Apache Flink to scale the company’s real-time analytics system that deduplicates over a million events and updates over a million counters per second.

The city of Warsaw used Apache Flink to build two main components of the VaVeL project, namely the Vehicle Movement Analyser and Vehicle Delay Prediction System.

Trackunit leverages Apache Flink as the stream processing framework of choice to build data pipelines for fleet management operations in the construction industry.

Kcell and GetInData developed a real time, stream analytics platform using Apache Flink® as a core component.

ING protects its banking customers with fraud detection powered by Apache Flink, adding new fraud detection models in real time with no downtime.

BetterCloud offers its customers a dynamic alerting system with Apache Flink.

To satisfy the need for accessible real-time stream processing, Tencent built Oceanus, a one-stop platform for real-time stream processing. Oceanus deploys Apache Flink^Ⓡ as its execution engine, hence realizing the benefits brought by Flink.

Streaming SQL with Apache Flink takes another step forward as Uber introduces its open source AthenaX platform for streaming SQL powered by Flink.