Gartner Research

Hype Cycle for Data Management, 2018

Published: 25 July 2018

ID: G00340279

Analyst(s): Donald Feinberg , Adam Ronthal

Summary

This Hype Cycle helps data and analytics leaders interested in data management strategies to understand the evolutionary pace of maturing and emerging data management technologies. There is a noticeable lack of new technologies entering the Hype Cycle, while many are approaching the plateau.

Table Of Contents

Analysis

  • What You Need to Know
  • The Hype Cycle
  • The Priority Matrix
  • Off the Hype Cycle
  • On the Rise
    • DataOps
    • Private Cloud dbPaaS
  • At the Peak
    • Machine Learning-Enabled Data Management
    • Data Classification
    • File Analysis
    • Time Series DBMS
    • Data as a Service
    • Data Catalog
    • SQL Interfaces to Cloud Object Stores
    • Event Stream Processing
    • In-Process HTAP
    • Blockchain
    • Multimodel DBMSs
  • Sliding Into the Trough
    • Data Preparation
    • Distributed Ledgers
    • Point-of-Decision HTAP
    • Data Lakes
    • Graph DBMSs
    • Spark
    • Information Stewardship Applications
    • Metadata Management Solutions
    • Cross-Platform Structured Data Archiving
    • Application Data Management
    • Key-Value DBMSs
    • Master Data Management
    • Wide-Column DBMSs
    • Operational In-Memory DBMS
    • Hadoop SQL Interfaces
    • iPaaS for Data Integration
    • In-DBMS Analytics
    • Logical Data Warehouse
  • Climbing the Slope
    • Document Store DBMSs
    • SaaS Archiving of Messaging Data
    • Data Integration Tools
    • Enterprise Information Archiving
    • Analytical In-Memory DBMS
    • Content Migration
  • Entering the Plateau
    • Database Encryption
    • Data Virtualization
    • In-Memory Data Grids
    • Database Platform as a Service
  • Appendixes
    • Hype Cycle Phases, Benefit Ratings and Maturity Levels

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