Confluent Blog

Running fully managed Apache Kafka® as a service brings many responsibilities that leading cloud providers hide well. There is a reason why cloud services  are so popular right now— companies realize

Data can originate in a number of different sources—transactional databases, mobile applications, external integrations, one-time scripts, etc.—but eventually it has to be synchronized to a central data warehouse for analysis

Do you have data you need to get into or out of Apache Kafka®? Kafka connectors are perfect for this. There are many connectors out there, usually for well-known and

Is event streaming or batch processing more efficient in data processing? Is an IoT system the same as a data analytics system, and a fast data system the same as

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

The latest ksqlDB release introduces long-awaited features such as tunable retention and grace period for windowed aggregates, new built-in functions including LATEST_BY_OFFSET, a peek at the new server API under

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

Single-cluster deployments of Apache Kafka® are rare. Most medium to large deployments employ more than one Kafka cluster, and even the smallest use cases include development, testing, and production clusters.

As the impact of COVID-19 (coronavirus) continues to spread, our top priority is the health and well-being of our customers, employees, and community. We are acutely aware that these are

Event stream processing solves many business challenges, from big data ingestion and data integration, to real-time data processing and IoT. It gives you the ability to analyze big data streams