Best Cloud Storage Services for Apache Kafka

Using OpenEBS in conjunction with Kubera is the optimal solution for storage needs in Kubernetes environments. OpenEBS stands out as the leading open source storage option for Kubernetes, recognized for its speed and efficiency. Kubera enhances OpenEBS Mayastor by providing a user-friendly graphical interface, along with APIs, automatic checks, configuration options, Active Directory authentication, built-in performance benchmarks, and additional operators to streamline upgrades and various other scenarios. Available at no cost, Kubera is offered by MayaData, which also provides round-the-clock support to help customers minimize operational expenses and simplify management. Kubera Propel, a cloud-native declarative data plane crafted in Rust, is built upon the foundational OpenEBS Mayastor technology. This innovative platform integrates cutting-edge technologies such as NVMe, SPDK, and new storage capabilities emerging within the Linux kernel. Independent benchmarks have demonstrated that OpenEBS, when governed by Kubera Propel, achieves remarkably low latency performance for databases and various workloads on Kubernetes, making it an excellent choice for developers and organizations alike. This combination not only enhances performance but also addresses the increasing demand for efficient and reliable storage solutions in modern computing environments.

Modern distributed messaging platforms like Kafka and Pulsar have established a robust Pub/Sub framework suitable for the demands of contemporary data-rich applications. Pravega takes this widely accepted programming model a step further by offering a cloud-native streaming infrastructure that broadens its applicability across various use cases. With features that ensure streams are durable, consistent, and elastic, Pravega also offers native support for long-term data retention. It addresses architectural challenges that earlier topic-centric systems such as Kafka and Pulsar have struggled with, including the automatic scaling of partitions and maintaining optimal performance despite a high volume of partitions. Additionally, Pravega expands the types of applications it can support by adeptly managing both small-scale events typical in IoT and larger data sets relevant to video processing and analytics. Beyond merely providing stream abstractions, Pravega facilitates the replication of application states and the storage of key-value pairs, making it a versatile choice for developers. This flexibility empowers users to create more complex and resilient data architectures tailored to their specific needs.