Understanding the Problem Space

RDM in Embedded and Real-Time Systems

RDM operates with tight memory and I/O constraints, supporting ACID transactions, multiple storage modes, and C/C++ API bindings. It provides a deterministic transaction engine, but concurrency control becomes complex when multiple threads perform simultaneous updates or schema operations. Incorrect usage of the RDM API often results in subtle deadlocks or silent failures that are difficult to trace without proper diagnostics.

// Potential issue: Nested transaction handling
rdm_begin_transaction(db);
rdm_update_record(db, table_id, data);
// Failing to commit or rollback in all code paths

Architectural Implications

Concurrency, Locking, and Resource Lifetimes

RDM uses internal locks to manage concurrent access, but its thread-safety guarantees require strict API discipline. Each thread must maintain its own session context, and failing to isolate handles or mismanaging session lifecycles leads to resource leakage and lock contention.

• Global vs local database handles are often confused, causing cross-thread contamination.
• Improper use of auto-commit or nested transactions can deadlock internal resource pools.
• Memory-mapped file mode, while performant, may delay write visibility across threads.

Diagnostics

How to Detect and Debug Deadlocks or Contention

To isolate concurrency issues in RDM:

• Enable verbose logging with `rdm_set_trace_level()` to monitor lock states.
• Track session identifiers to ensure thread-to-session isolation.
• Instrument all transaction entry/exit points with logging to identify orphaned transactions.
• Use `rdm_db_status()` to check for stale or blocked handles.

// Enable diagnostics
rdm_set_trace_level(RDM_TRACE_LOCKS | RDM_TRACE_TRANSACTIONS);

Common Pitfalls

Mismanagement of Sessions and Transactions

• Reusing database handles across threads without synchronization.
• Failure to call `rdm_end_transaction()` on all code paths (e.g., exceptions).
• Starting multiple overlapping transactions in the same thread.
• Mixing synchronous and asynchronous modes without context tracking.

Step-by-Step Fixes

Hardening Your RDM Implementation

1. Ensure every thread initializes its own database session and handles independently.
2. Wrap transaction logic with structured error handling to guarantee commit/rollback.
3. Use mutexes when multiple threads operate on shared datasets or schema.
4. Regularly call `rdm_checkpoint()` if using on-disk mode to flush buffers safely.
5. Isolate schema updates to single-threaded operations during maintenance windows.

// Transaction safety wrapper
rdm_begin_transaction(db);
bool success = perform_operations();
if (success)
  rdm_end_transaction(db, RDM_COMMIT);
else
  rdm_end_transaction(db, RDM_ROLLBACK);

Best Practices

Reliable Multi-Threaded RDM Deployment

• Design thread affinity for RDM sessions; never share handles arbitrarily.
• Implement watchdogs that monitor for long-running or stalled transactions.
• Use in-memory mode only when deterministic flushing and snapshotting are properly handled.
• Benchmark with realistic thread loads to simulate production timing behavior.
• Follow RDM's official concurrency model—favor message-passing patterns over shared memory writes.

Conclusion

Raima Database Manager excels in deterministic, embedded environments, but introduces intricate concurrency and consistency challenges in multi-threaded deployments. Senior engineers must enforce strict session and transaction boundaries, ensure isolation across threads, and use diagnostic hooks to monitor lock and transaction states. A disciplined architectural approach—paired with code-level defensive practices—can ensure RDM delivers both performance and stability at scale.

FAQs

1. Can RDM be used safely in multi-threaded applications?

Yes, but each thread must maintain its own session and handle set. Thread-safety is not guaranteed if handles are shared or improperly synchronized.

2. What causes deadlocks in RDM?

Deadlocks typically occur due to uncommitted overlapping transactions, shared schema access, or recursive locking within the same session.

3. How do I trace memory leaks in RDM?

Use `rdm_db_status()` and enable RDM trace logs. Ensure all transactions and sessions are explicitly closed and handles are dereferenced.

4. Does RDM support schema migration at runtime?

Limited support exists, but schema changes should be performed in isolated threads with all other sessions paused or quiesced.

5. How can I improve RDM write performance?

Use memory-mapped storage, batch updates inside a single transaction, and call `rdm_checkpoint()` periodically for optimal flush timing.