Difference Between 4D and ActivePivot

Abhijat SarariAbhijat Sarari
3 min read

Introduction

Choosing the right database or analytical platform is crucial for business efficiency and data management. 4D and ActivePivot are two distinct technologies that cater to different needs. While 4D is a relational database and application development platform, ActivePivot is a real-time OLAP (Online Analytical Processing) engine designed for complex data analysis. This article provides an in-depth comparison of both, along with examples and use cases.

What is 4D?

4D is a relational database management system (RDBMS) with an integrated development environment (IDE). It is widely used for business applications, offering scalability, flexibility, and cross-platform support.

Key Features of 4D:

  • Relational Database: Supports SQL-based queries and structured data storage.

  • Integrated Development Environment: Facilitates application development and deployment.

  • Cross-Platform Support: Works on macOS and Windows.

  • Scalability: Suitable for small to medium-sized enterprises.

  • Built-in Web Server: Enables web application development.

What is ActivePivot?

ActivePivot, developed by ActiveViam, is an in-memory OLAP engine designed for real-time data aggregation and analytics. It is primarily used in financial services, risk management, and supply chain analytics.

Key Features of ActivePivot:

  • Real-Time Data Processing: Enables instant data aggregation and analytics.

  • Multi-Dimensional Analysis: Supports complex queries on large datasets.

  • In-Memory Computation: Provides high-speed performance for analytics.

  • Scalable and Distributed: Can handle large-scale data environments.

  • Predictive and Prescriptive Analytics: Integrates with AI/ML workflows.

Comparison Table

Feature4D DatabaseActivePivot
TypeRelational DatabaseIn-Memory OLAP Engine
Primary Use CaseApplication development & data storageReal-time analytics & business intelligence
PerformanceGood for transactional applicationsExtremely fast due to in-memory processing
ScalabilityModerate, suitable for SMBsHigh, optimized for large-scale analytics
Data ModelRelational (SQL)Multi-dimensional cubes
Querying MechanismSQL-based queriesMDX, Java, and custom APIs
Fault ToleranceReplication & backupsDistributed fault-tolerant architecture
IntegrationWeb, mobile, desktop appsAI, ML, financial applications

Example Use Cases

Example: 4D for Business Application Development

Begin SQL
   SELECT * FROM Customers WHERE Age > 30
End SQL;

This example demonstrates how 4D queries a customer database for users above 30 years old.

Example: ActivePivot for Real-Time Risk Analytics

ActivePivotManager manager = new ActivePivotManager();
manager.createCube("RiskAnalysis");
manager.aggregate("TotalRisk", "SUM");

This example showcases ActivePivot's real-time data aggregation for financial risk management.

When to Use 4D vs. ActivePivot

ScenarioBest Choice
Building a business application with an embedded database4D
SQL-based relational data management4D
Real-time financial risk analyticsActivePivot
Big data aggregation for instant insightsActivePivot
Multi-dimensional OLAP analysisActivePivot

Conclusion

4D and ActivePivot serve different purposes—4D is ideal for relational data storage and business application development, whereas ActivePivot excels in real-time, in-memory analytics for complex datasets. Selecting the right tool depends on the application's needs, whether it requires a traditional RDBMS or an advanced OLAP solution.

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Abhijat Sarari
Abhijat Sarari