Who should use DDS?

Choosing the right middleware is a critical architectural decision. DDS is not a “one-size-fits-all” solution, but it excels in specific, demanding environments. If your system requires real-time performance, scalability, and independence from central servers, DDS is likely the optimal choice.

Here are the key indicators that your project will benefit from DDS:

1. You Have a Dynamic Network Topology

Does your system involve devices that need to join and leave the network spontaneously?

  • Example: An air traffic control system, a fleet of autonomous mobile robots (AMRs), or a modular industrial machine.
  • DDS Advantage: With built-in discovery, DDS handles dynamic presence automatically. You don’t need to reconfigure the network every time a sensor is added or a robot goes offline for maintenance.

2. You Need High Performance & Low Latency

Do you need to transmit large volumes of data or operate logic loops in the millisecond (or microsecond) range?

  • Example: Radar signal processing, vehicle telemetry, or high-frequency trading.
  • DDS Advantage: DDS implementations typically use UDP/IP with efficient binary serialization (CDR), offering near bare-metal performance. Zero-copy mechanisms further reduce latency by minimizing memory operations.

3. Your System Must Be Resilient (No Single Point of Failure)

Can your system afford to stop working if a central server crashes?

  • Example: Defense systems, critical healthcare monitoring, or power grid protection relays.
  • DDS Advantage: The peer-to-peer, brokerless architecture distributes intelligence across the network. If one node fails, the rest of the system continues to operate unaffected. Redundancy is built into the protocol.

4. You Need Evolving Data Models

Will your data structures change over the lifecycle of the project?

  • Example: An automotive system where sensor data schemas evolve with new vehicle models.
  • DDS Advantage: DDS is data-centric. Its Extensible and Dynamic Topic Types (X-Types) allow systems to handle data type evolution gracefully, enabling newer and older versions of applications to interoperate seamlessly.

When to Consider Alternatives

While DDS is powerful, other patterns may be better suited for specific scenarios:

  • Heavy Database-Centric Workloads: If your primary goal is to store and retrieve static records (CRUD operations) rather than distribute real-time state, a traditional SQL/NoSQL Database is often more appropriate.
  • Simple Web Applications: For standard client-server web apps where real-time push is not critical, REST or GraphQL APIs over HTTP are typically simpler to implement and debug.
  • Simple Request-Response: If your application follows a strictly linear command-response flow without unparalleled data distribution needs, gRPC or raw RPC mechanisms might be sufficient.