In-Memory Database Tiering for Storage Cost Reduction

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Solution Overview

Problem

In-memory databases face inefficiencies due to storage of less relevant data, which reduces their performance and requires costly high-speed memory allocation, while historical data occupies valuable space and is less frequently accessed.

Innovation Solution

Implementing a method to classify data into logical tiers based on relevance, where current data is stored in high-performance memory and historical data is moved to lower-cost, lower-performance storage, with controlled access ensuring only relevant data is accessed, and data is transferred between tiers based on classification rules.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If historical data is stored in in-memory database, then data accessibility is maintained, but storage cost and memory usage increase

Engineering Contradiction:

Improvedata accessibilityVSAvoidmemory storage capacity

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The patent segments the database into multiple logical tiers (e.g., hot, warm, cold tiers) based on data age and access frequency. Current frequently accessed data remains in high-speed in-memory storage, while historical data is automatically moved to lower-cost storage media, thereby maintaining accessibility for important data while reducing overall memory consumption.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically changes storage parameters by transitioning data between different logical tiers based on age and access patterns. Data automatically moves from high-speed memory to lower-cost storage as it ages and becomes less frequently accessed, optimizing the balance between accessibility and storage cost.

Inventive Principle:

Principle #35Parameter changes

2Speed

If high-speed memory is allocated for all data, then data access speed is improved, but storage cost increases

Engineering Contradiction:

Improvedata access speedVSAvoidmemory allocation cost

Core Design Contradiction:

SpeedVSQuantity of substance

Solution Approach 1:

The patent applies local quality by providing high-speed memory access only to specific portions of data (current and frequently accessed data) rather than uniformly to all data. Historical and less frequently accessed data is stored in lower-cost media, creating a differentiated storage quality that matches actual access requirements.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically adjusts data placement between logical tiers based on changing access patterns and data age. Data that was previously historical may be promoted back to high-speed memory if access patterns change, creating a dynamic optimization that adapts to actual usage rather than using static allocation.

Inventive Principle:

Principle #15Dynamics

3Productivity

If all data is kept in in-memory database, then query performance is maintained, but storage efficiency decreases

Engineering Contradiction:

Improvequery performanceVSAvoidstorage cost

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The system performs preliminary classification and tiering of data based on predicted access patterns and data age. By pre-positioning data in appropriate logical tiers before queries are executed, the system ensures that frequently accessed data is already in high-speed memory, maintaining query performance without keeping all data in memory.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10885062B2Providing database storage to facilitate the aging of database-accessible data

Publication Date: 2021.01.05 SAP SE

AI summary

Persisting data in logical tiers of an in-memory database based on aging rules of the database system. The database system can be configured to age data by moving the data from a first logical tier supporting high performance data access to a second logical tier supporting lower performance data access, thereby improving the operational efficiency of the database system.