Gartner Research

Protecting Big Data in Hadoop

Published: 14 July 2014

ID: G00263963

Analyst(s): Joerg Fritsch , Ramon Krikken

Summary

The race for dominance in the Hadoop security market niche is on. Vendors have realized that end users want to regain the controls that they have been using to protect their data in relational databases and are working hard to meet customers' expectations.

Table Of Contents

Analysis

  • Navigate the Lands of Big Data Security
  • Key Issues in Hadoop Security
    • Infrastructure Security
    • Traditional Database Security
    • Need to Protect vs. Need to Share
  • Hadoop Architecture and Where Security Can Go
    • Hadoop Infrastructure Security
    • The Black Box: Cluster Management Security
    • Controls That Are Part of Hadoop Components or Security Services
    • Externalized Data Security: Data Services, Discovery, Masking, Redaction and Tokenization
  • Status of Hadoop Security
    • OSS Hadoop Security Has Soft Spots
    • Hadoop Security Implements Strong Access Controls
    • Hadoop Security Is Fragmented
  • Strengths
  • Weaknesses

Guidance

  • Keep the Lock-In Minimal
  • Prefer Inherent Security Before Packaged Security
  • Externalize Data Security
  • Harness the Log and Audit Sprawl
  • Compensate Soft Spots With Traditional Safeguards

The Details

  • Approaches to Hadoop Security
    • Focused Approaches
    • Adaptive Approaches
  • Selected Case Studies for Hadoop Security
    • Externalized: Data Redaction With ETL and Sqoop
    • Inherent/Packaged: RBAC All the Way Out
    • Vendors

Notes

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