Confluent has released its quarterly update package Q1 ’22. The collection includes a number of innovations for the cloud-native service of the data streaming provider Confluent Cloud. Confluent is a commercial tool for managing and processing data streams and is based on the open source software Apache Kafka.
Extended connections
The number of possible connections to external tools via connectors has increased significantly: Confluent Cloud will offer more than 50 connectors in the future, more than twice as many as before. This makes it the only Kafka cloud service with more than 50 connections, according to the company.
Both source and sink data connectors are new, including to ActiveMQ source, Databrick’s Delta Lake sink and Google’s BigTable sink. Confluent provides the full list of connected services in the documentation. The connection to the observability platforms Datadog and Prometheus is also new.
Elasticity in throughput
The cluster options have also been revised: The use of the service should become more cost-efficient, customers can reduce the capacity provided more flexibly as needed. Confluent calls this Dedicated Cluster. This new offering is demand-based, allowing capacity to be scaled as needed through either the Confluent Cloud UI, CLI, or API.
schema linking
With Schema Linking, Confluent customers now also have real-time schema linking to ensure data quality. This allows them to more easily manage trusted data streams across cloud and hybrid environments. In combination with cluster linking, it is thus possible to easily guarantee high data integrity throughout the company.
The full list of updates to the Confluent Q1 ’22 package is available on the vendor’s website.
(jvo)