Running clusters on the cloud
Build and Manage clusters effortlessly and embrace scalability-driven abilities.
Implementing the Apache Kafka platform with built-in features for horizontal scalability and high-throughput, low latency allows geographically dispersed data streams and stream-processing applications. Use tools built for managed Kafka that helps to form real-time, centralized, and privately accessible data buses and scale cluster capacity automatically.
Apache Kafka offers a high throughput and availability using a distributed cluster of servers.
Apache Kafka uses management console monitoring statistics to give a real-time view of the data stream.
Apache Kafka output data can be stored parallel to Apache Hadoop during the Apache Kafka operations.
As everything revolves around data, transmitting data from one place to another is challenging. Doing this with real-time data is even more challenging. So to solve this problem, there comes a perfect distributed data streaming platform called Kafka.
Apache Kafka is a stream processor taking continuous streams of data from input topics, performs processing on this input, and produces continuous streams of data to output topics in a simplified version.
Empowering processing at scale
Kafka-driven applications are scalable, which improves and enables seamless cluster setup and deployment
End-to-End managed solutions for supporting enterprises facilitate seamless migration with zero downtime.
Empower automated and managed data integration with Managed Apache Kafka as a Service
Monitor and gain insights over deployed clusters and take action in real-time.
Build and Manage clusters effortlessly and embrace scalability-driven abilities.
Building optimized Kafka infrastructure
Facilitate and build completely managed parallel and integrated operations with Dataproc
Amazon Managed Streaming for Apache Kafka
Run streaming data pipelines efficiently and analytics in real-time with Amazon MSK.
Azure HDInsight Solutions
Enterprises can utilize HD insight abilities for easy administration and configuration of Spark clusters.
Apache Flink
Apache NiFi
Apache Spark
Event-Driven Architecture
Apache Flink is useful in efficient disk spilling, network transfers, and reduction of Garbage Collection
Apache NiFi provides an easy-to-use, powerful, and reliable system to process and distribute the data over several resources. NiFi helps to route and processing data from any source to any destination
Apache Spark is a high-performing large-scale analytics and data processing engine that offers high batch and interactive processing performance.
Event-Driven Architecture (EDA) is a model or an architectural paradigm for software that supports the production, detection, consumption of, and reaction to the event or a significant system state change. This structure consists of event creators and event consumers
Adapt to new evolving tech stack solutions to ensure informed business decisions.
Achieve Unified Customer Experience with efficient and intelligent insight-driven solutions.
Leverage the True potential of AI-driven implementation to streamline the development of applications.
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