Auto Database Integration
Company Size
1,000+
Product
- Hazelcast IMDG
- Auto Database Integration (ADBI)
Tech Stack
- Java
- Hazelcast Portable interface
- Oracle
- MySQL
- PostgreSQL
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Digital Expertise
- Productivity Improvements
Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Application Infrastructure & Middleware - Database Management & Storage
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Functions
- Business Operation
Services
- Software Design & Engineering Services
- System Integration
About The Customer
The customer is a logistics company that operates on a global scale, tracking logistics events and managing a complex system that has evolved over time. The company deals with a diverse set of data sources, including almost 50 different relational databases running Oracle, MySQL, and PostgreSQL. The company's system has grown in terms of functional features, geographical locality, and business arrangements, leading to a constant need for new features and data model changes. The company aims to reduce maintenance costs, improve performance, and enable more interactive data exploration.
The Challenge
The logistics company faced significant challenges in managing an evolving data model across a large, heterogeneous set of data sources. With almost 50 different relational databases running Oracle, MySQL, and PostgreSQL, the company needed to address performance issues and enable more interactive data exploration. The introduction of a Hazelcast in-memory data grid as a distributed cache improved data retrieval latency but added a new layer of maintenance complexity. The company needed to keep the data model of the data grid in sync with the data sources as the relational database schemas changed over time.
The Solution
To address the maintenance problem, the company implemented Auto Database Integration (ADBI) to streamline the process of keeping the data model of the Hazelcast IMDG in sync with the relational database sources. At design time, ADBI connects to the relational databases, analyzes the metadata of the tables, and generates the necessary Java POJOs to interact with both the databases and the in-memory grid. ADBI can analyze metadata from all major database engines, making it suitable for managing a heterogeneous set of sources. At run-time, ADBI provides the functionality to feed data from the sources to the data grid, leveraging the Hazelcast Portable interface. This allows the data grid to serve as a vessel for the data without any modifications. Java applications using ADBI can access data from both the grid and the relational databases using Java Streams, enabling seamless optimization and reducing the need for business logic rewrites.
Operational Impact
Quantitative Benefit
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