Struggling to choose between HortonWorks Data Platform and Cloudera CDH? 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, Cloudera CDH is a Ai Tools & Services product tagged with hadoop, hdfs, yarn, spark, hive, hbase, impala, kudu.
Its standout features include HDFS - Distributed and scalable file system, YARN - Cluster resource management, MapReduce - Distributed data processing, Hive - SQL interface for querying data, HBase - Distributed column-oriented database, Impala - Massively parallel SQL query engine, Spark - In-memory cluster computing framework, Kudu - Fast analytics on fast data, Cloudera Manager - Centralized management and monitoring, and it shines with pros like Open source and free to use, Includes many popular Hadoop ecosystem projects, Centralized management and monitoring, Pre-configured and tested combinations of components, Active development and support from Cloudera.
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.
Cloudera CDH (Cloudera Distribution Including Apache Hadoop) is an open source data platform that combines Hadoop ecosystem components like HDFS, YARN, Spark, Hive, HBase, Impala, Kudu, and more into a single managed platform.