tanszek:oktatas:iss_t:software_integration
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| tanszek:oktatas:iss_t:software_integration [2026/02/15 22:11] – [Limitations] knehez | tanszek:oktatas:iss_t:software_integration [2026/02/15 22:18] (current) – [Data Sharing] knehez | ||
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| ===== Data Sharing ===== | ===== Data Sharing ===== | ||
| - | A simple approach to integration is data sharing. | + | A simple approach to integration is data sharing. Data sharing–based integration aims to transfer and share data between systems. This enables individual systems to access and utilize data stored in other systems. |
| - | + | ||
| - | Data sharing–based integration aims to transfer and share data between systems. | + | |
| - | This enables individual systems to access and utilize data stored in other systems. | + | |
| Data sharing can take several forms: | Data sharing can take several forms: | ||
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| ===== File-Based Data Sharing ===== | ===== File-Based Data Sharing ===== | ||
| - | The most fundamental method of data sharing. | + | The most fundamental method of data sharing. One application writes data, while another application reads data from the same file. The data files are stored in a central location — such as a shared folder (e.g., NFS) or an (S)FTP server. The information flow is unidirectional: |
| - | + | ||
| - | One application writes data, while another application reads data from the same file. | + | |
| - | + | ||
| - | The data files are stored in a central location — such as a shared folder (e.g., NFS) | + | |
| - | or an (S)FTP server. | + | |
| - | + | ||
| - | The information flow is unidirectional: | + | |
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| * Platform-independent connectivity (e.g., JDBC, ODBC) | * Platform-independent connectivity (e.g., JDBC, ODBC) | ||
| * Multiple instances of identical components may access the same database | * Multiple instances of identical components may access the same database | ||
| - | |||
| * Synchronization issue: Who processes the next record in the queue? | * Synchronization issue: Who processes the next record in the queue? | ||
| * However, it can be an ideal solution for data collection scenarios. | * However, it can be an ideal solution for data collection scenarios. | ||
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| ==== Limitations ==== | ==== Limitations ==== | ||
| - | * Not real-time by default. | + | * Not real-time by default. If one application writes to the database, another application does not automatically receive notification. |
| - | | + | |
| - | + | * Database notification mechanisms (e.g., PostgreSQL LISTEN and NOTIFY) | |
| - | Possible solutions: | + | * Triggers |
| - | + | * Polling mechanisms | |
| - | | + | |
| - | * Triggers | + | |
| - | * Polling mechanisms | + | |
| * Security considerations: | * Security considerations: | ||
| - | |||
| * Lack of well-defined interfaces — this approach provides only data-level integration. | * Lack of well-defined interfaces — this approach provides only data-level integration. | ||
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| * When strict decoupling between systems is a design goal. | * When strict decoupling between systems is a design goal. | ||
| * In highly scalable cloud-native environments where message-based communication is preferred. | * In highly scalable cloud-native environments where message-based communication is preferred. | ||
| + | |||
| + | ===== Integration Strategy Comparison ===== | ||
| + | |||
| + | ^ Aspect ^ File-Based Integration ^ Database-Based Integration ^ Message Queue-Based Integration ^ | ||
| + | | Coupling | Tight coupling (shared file format) | Tight to medium coupling (shared schema) | Loose coupling | | ||
| + | | Communication Style | Batch, unidirectional | Data-level sharing | Asynchronous message exchange | | ||
| + | | Real-Time Capability | No | Not by default | Yes (naturally asynchronous) | | ||
| + | | Scalability | Limited | Moderate | High | | ||
| + | | Monitoring | Difficult | Database-level monitoring | Built-in queue monitoring (DLQ, metrics) | | ||
| + | | Complexity | Low initial complexity | Medium | High | | ||
| + | | Transaction Support | No native support | Strong ACID support | Depends on message broker | | ||
| + | | Typical Use Case | Periodic data exchange | Shared enterprise systems | Distributed / cloud-native systems | | ||
| + | | Interface Definition | File format agreement | Shared database schema | Message contract / schema definition | | ||
| + | | Cloud-Native Suitability | Low | Medium | High | | ||
tanszek/oktatas/iss_t/software_integration.1771193494.txt.gz · Last modified: 2026/02/15 22:11 by knehez