Struggling to choose between HortonWorks Data Platform and Google Cloud Dataproc? Both products offer unique advantages, making it a tough decision.
HortonWorks Data Platform is a Ai Tools & Services solution with tags like hadoop, big-data, analytics.
It boasts features such as Distributed storage and processing using Hadoop, Real-time data processing with Storm, Data governance and security, Simplified management and monitoring, Integration with R, Python, Spark and more and pros including Open source and free, Scalable and flexible, Supports wide variety of workloads, Enterprise-grade security and governance, Large ecosystem of integrations.
On the other hand, Google Cloud Dataproc is a Ai Tools & Services product tagged with hadoop, spark, big-data, analytics.
Its standout features include Managed Spark and Hadoop clusters, Integrated with other GCP services, Autoscaling clusters, GPU support, Integrated monitoring and logging, and it shines with pros like Fast and easy cluster deployment, Fully managed so no ops work needed, Cost efficient, Integrates natively with other GCP services.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
HortonWorks Data Platform (HDP) is an open source distributed data management platform based on Apache Hadoop. It provides scalable and flexible data storage and processing for big data workloads.
Google Cloud Dataproc is a fast, easy-to-use, fully-managed cloud service for running Apache Spark and Apache Hadoop clusters in a simple, cost-efficient way.