Gartner Research

How to Select In-Memory Computing Technologies for Big Data

Published: 15 April 2015

ID: G00277205

Analyst(s): Kurt Schlegel , Keith Guttridge , Massimo Pezzini , Roxane Edjlali , Nick Heudecker

Summary

To tackle digital business moments, organizations often must adopt in-memory computing capabilities to enable real-time analytics of ever-larger and faster-moving datasets. However, it's not so obvious for information management leaders which IMC technologies fit best with their business needs.

Table Of Contents
  • Key Challenges

Introduction

Analysis

  • Use High-Performance Messaging Infrastructure for Low-Latency and High-Scale Transport of Data on the Move
  • Adopt Event Stream Processing for Real-Time Pattern Detection Within Data on the Move
  • Endorse In-Memory Data Grids to Absorb Large Volumes of Data on the Move
  • Leverage In-Memory DBMS for Faster and Deeper Analysis of Data at Rest
  • Deploy In-Memory Analytics to Enable Self-Service Analytics of Data at Rest
  • Consider the Adoption of IMC Platforms Combining Multiple Capabilities

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