Gartner Research

Comparing Four Hadoop Integration Architectures

Published: 03 June 2016

ID: G00303737

Analyst(s): Mei Selvage

Summary

Hadoop is the backbone for big data analytics, but integration remains a key challenge to its success. Integration specialists, architects and IT managers should evaluate four architectures — batch, data virtualization, replication and messaging — to reap the maximal return for your Hadoop.

Table Of Contents

Comparison

  • Hadoop Ecosystem
    • Data Source Tier
    • Integration Tier
    • Processing Tier
    • Analytics Tier
  • Assessment Criteria for Comparing Four Integration Architectures
  • High-Level Comparison of Four Integration Architectures

Analysis

  • Batch Data Movement
  • Data Virtualization
  • Replication
  • Messaging

Guidance

  • Apply the Separation-of-Concerns Design Principle
  • Refresh the Enterprise Integration Strategy
  • Treat Hadoop as a Component of the LDW
  • Perform an Architectural Trade-Off Analysis and Document Justifications
  • Establish the Data Quality Program
  • Manage Metadata in Hadoop and Beyond

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