HortonWorks Data Platform vs Amazon EMR

Struggling to choose between HortonWorks Data Platform and Amazon EMR? 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, Amazon EMR is a Ai Tools & Services product tagged with hadoop, spark, big-data, distributed-computing, cloud.

Its standout features include Managed Hadoop and Spark clusters, Supports multiple big data frameworks like Apache Spark, Apache Hive, Apache HBase, and more, Automatic scaling of compute and storage resources, Integration with AWS services like Amazon S3, Amazon DynamoDB, and Amazon Kinesis, Supports custom applications and scripts, Provides easy cluster configuration and management, and it shines with pros like Fully managed big data platform, Scalable and fault-tolerant, Integrates with other AWS services, Reduces the need for infrastructure management, Flexible and supports various big data frameworks.

Feature	HortonWorks Data Platform	Amazon EMR
Overall Score	N/A	N/A
Primary Category	Ai Tools & Services	Ai Tools & Services

Product Overview

HortonWorks Data Platform

Description: 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.

Amazon EMR

Description: Amazon EMR is a cloud-based big data platform for running large-scale distributed data processing jobs using frameworks like Apache Hadoop and Apache Spark. It manages and scales compute and storage resources automatically.

Key Features Comparison

HortonWorks Data Platform Features

• 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

Amazon EMR Features

• Managed Hadoop and Spark clusters
• Supports multiple big data frameworks like Apache Spark, Apache Hive, Apache HBase, and more
• Automatic scaling of compute and storage resources
• Integration with AWS services like Amazon S3, Amazon DynamoDB, and Amazon Kinesis
• Supports custom applications and scripts
• Provides easy cluster configuration and management

Pros & Cons Analysis

HortonWorks Data Platform

Pros

• Open source and free
• Scalable and flexible
• Supports wide variety of workloads
• Enterprise-grade security and governance
• Large ecosystem of integrations

Cons

• Complex to set up and manage
• Requires expertise in Hadoop and big data
• Not as user friendly as some alternatives
• Limited support options

Amazon EMR

Pros

• Fully managed big data platform
• Scalable and fault-tolerant
• Integrates with other AWS services
• Reduces the need for infrastructure management
• Flexible and supports various big data frameworks

Cons

• Can be more expensive than self-managed Hadoop clusters for long-running jobs
• Vendor lock-in with AWS
• Limited control over the underlying infrastructure
• Complexity in managing multiple big data frameworks

Pricing Comparison

HortonWorks Data Platform

• Open Source
• Subscription-Based

Amazon EMR

• Pay-As-You-Go