Live demo: Kafka streaming in 10 minutes on Confluent | Register now


Scrapinghub Accelerates Next-Generation Web Scraping Service with Confluent Cloud

Each day thousands of companies and more than a million developers rely on Scrapinghub tools and services to extract the data they need from the web. To strengthen its position as a market leader, Scrapinghub recently launched a new product, AutoExtract, that provides customers with AI-enabled, automated web data extraction at scale. Scrapinghub built AutoExtract on Confluent Cloud running on Google Cloud Platform (GCP), with an Apache Kafka®-based, event-streaming backbone for its service architecture. These technologies were chosen to shorten time to market, and to ensure reliability and scalability.


Accelerate the delivery of a next-generation web scraping service, capable of handling growing customer demand with no downtime.


Use Confluent Cloud and Apache Kafka to implement a reliable, scalable event-streaming backbone that links web crawlers with AI-enabled data extraction components.


  • Deployment time halved
  • Initial setup completed in minutes
  • 100% uptime post-launch
  • Latencies minimized with no cloud vendor lock-in

Ian Duffy

DevOps Engineer

A key advantage of Confluent Cloud in delivering AutoExtract is time to market. We didn’t have to set up a Kafka cluster ourselves or wait for our infrastructure team to do it for us. With Confluent Cloud we quickly had a state-of-the-art Kafka cluster up and running perfectly smoothly. And if we run into any issues, we have experts at Confluent to help us look into them and resolve them. That puts us in a great position as a team and as a company.


Scrapinghub Accelerates Next-Generation Web Scraping Service with Confluent Cloud

Why Scrapinghub’s AutoExtract Chose Confluent Cloud for Their Apache Kafka Needs

More Customer Stories


8×8 Powers Real-Time Contact Center Analytics with Confluent.


Ticketmaster Leverages Confluent to Reduce Development Friction and Boost Machine Learning.

UC San Diego

UC San Diego Reduces Time-to-Value for Core Business Processes with Integration Layer Built on Data In Motion With Confluent