In-memory computing stores information in main RAM instead of slower disk drives, enabling rapid data analysis and operations, particularly benefiting industries like banking and utilities. Its popularity is rising due to decreasing memory costs and the increasing demand for speed in processing. However, challenges such as lack of standards, high migration costs, and data persistence concerns remain.

1. In Memory
Computing
Presented By:
Kiran Ghanta

2.  What is In Memory Computing?
 Storage of information in the main random access memory (RAM)
 Rather than in complicated RDBMS operating on comparatively slow disk drives
 What are the Uses of In Memory Computing?
 Helps business customers, like, banks and utilities, to
 Quickly analyse patterns
 Analyse massive data volumes on the fly
 Perform their operations quickly
 Why In Memory Computing increasingly popular now a days?
 The drop in memory prices in the present market
 Need for “peed is the dri ing fa tor
 Why is it time for in-memory computing?
 DRAM costs are dropping about 30% every 12 - 18 months
 Things are getting bigger, and costs are getting lower

3. General Architecture

5. In Memory Computing
Myths

7. In Memory Computing
Drivers

9. In Memory Computing
Challenges

10.  Lack of standards:
 No specific standards for developing IMC solutions
 Companies are providing their offerings in ad hoc manner
 Compatibility issues among solutions from other vendors
 Migration:
 Costs associated with IMC systems are comparatively high
 It is a time consuming process.
 Persistence:
 We are talking a out DRAM: the D stands for destru ti e
 It doesn’t hold data, if e lose po er

11. In Memory Computing
Action Plan

13. In Memory Computing
Platforms and Applications

15. References :
http://timoelliott.com/blog/2013/04/the-business-impact-of-in-memory-computing-from-run-to-
transform.html
http://timoelliott.com/blog/2013/04/how-and-why-to-create-an-in-memory-action-plan.html