In-Memory Data Warehouse Platform for Real-Time Analytics
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Solution Overview
Problem
Traditional database management systems are inadequate for handling both transactional and analytical workloads simultaneously, requiring separate databases and extensive data transformation, which leads to lagging performance and reduced ability to monitor organizational performance or generate timely forecasts.
Innovation Solution
An in-memory data warehouse platform that combines transactional and analytical workloads in a single database, eliminating the need for data transformation and providing real-time reporting capabilities through a hybrid structure that supports advanced analytics and views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional database management systems are used for analytical workloads, then separate databases and data transformation are required, but system complexity and processing time increase
Solution Approach 1:
The patent combines OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) workloads into a single database system. The database engine simultaneously handles both analytical queries and transactional operations without requiring separate database instances, data replication, or extensive ETL (Extract, Transform, Load) processes, thereby reducing system complexity while maintaining analytical processing speed.
Solution Approach 2:
The database system is designed with multi-functionality to serve dual purposes: it performs transactional operations (inserts, updates, deletes) and analytical operations (complex queries, aggregations, forecasting) within the same engine. This universal design eliminates the need for specialized separate systems and simplifies the overall architecture.
2Reliability
If separate databases are used for transactional and analytical workloads, then workload isolation is achieved, but data transformation and loading effort increase
Solution Approach 1:
The patent extracts the fundamental assumption that separate databases are needed for workload isolation. Instead, it implements logical separation and optimization within a single database engine, using techniques such as query optimization, memory management, and execution plans that allow simultaneous handling of transactional and analytical workloads without physical data replication or transformation.
Solution Approach 2:
The database engine provides self-service capabilities by automatically managing resource allocation, query optimization, and workload balancing between transactional and analytical operations. This eliminates the need for manual data transformation and loading processes that would otherwise be required to maintain separate databases.
3Quantity of substance
If data is stored in disk drive devices, then storage capacity is increased, but query performance decreases
Solution Approach 1:
The patent changes the physical state parameter of data storage by implementing an in-memory database architecture where data is primarily stored in volatile memory (RAM) rather than on disk drives. This parameter change from magnetic/optical storage to electronic memory dramatically increases query performance while maintaining sufficient storage capacity for analytical workloads. The system manages memory resources to accommodate large datasets required for forecasting and planning.
Data Source
AI summary
Various embodiments herein each include at least one of systems, methods, and software for in memory data warehouse planning and broadcasting. Some embodiments include an in memory database having a set of define database table views that provide a virtual data model upon which services execute for various purposes including planning, simulation, and broadcasting of generated reports and other document. These services are executed within a computing environment of the in memory database and can be configured and grouped into applications and processes. Such embodiments eliminate system performance bottlenecks and provide a platform upon which “extreme” application performance can be obtained.