Building Confluent Cloud – Here’s What We’ve Learned
In July 2017, Confluent launched a private preview of what would later be known as Confluent Cloud. This platform as a service product has grown rapidly; less than three years
In July 2017, Confluent launched a private preview of what would later be known as Confluent Cloud. This platform as a service product has grown rapidly; less than three years
As enterprises move more and more of their applications to the cloud, they are also moving their on-prem ETL pipelines to the cloud, as well as building new ones. There
Less than six months ago, we announced support for Microsoft Azure in Confluent Cloud, which allows developers using Azure as a public cloud to build event streaming applications with Apache
This article shows how you can offload data from on-premises transactional (OLTP) databases to cloud-based datastores, including Snowflake and Amazon S3 with Athena. I’m also going to take the opportunity
Following Google’s announcement to provide leading open source services with a cloud-native experience by partnering with companies like Confluent, we are delighted to share that Confluent Cloud is now available
Potential advantages of hybrid cloud architectures include avoiding vendor lock-in, increasing system resilience, optimizing costs, and inducing price competition among cloud providers. Hybrid cloud architectures require the ability to securely
Today, we are proud to make Confluent Cloud available to companies leveraging the Microsoft Azure ecosystem of services, in addition to the previous rollouts on Google Cloud Platform (GCP) and
We recently launched a new artificial intelligence (AI) data extraction API called Scrapinghub AutoExtract, which turns article and product pages into structured data. At Scrapinghub, we specialize in web data
Go from zero to production on Apache Kafka® without talking to sales reps or building infrastructure Apache Kafka is the standard for event-driven applications. But it’s not without its challenges,
As a distributed system for collecting, storing, and processing data at scale, Apache Kafka® comes with its own deployment complexities. Luckily for on-premises scenarios, a myriad of deployment options are
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