Horizontal Throughput Scaling

Definition ∞ Horizontal throughput scaling is a method for increasing the processing capacity of a system by adding more machines or nodes to handle workload in parallel. Instead of upgrading individual components, this approach distributes tasks across a larger number of less powerful units. It is a common strategy in distributed systems to manage growing transaction volumes and user demand. This scaling technique enhances the overall system’s ability to process data.
Context ∞ In blockchain technology, horizontal throughput scaling is a critical objective for networks aiming to process a high volume of transactions per second. A key discussion involves implementing solutions like sharding, where the network state and transaction processing are divided among multiple independent chains or partitions. Future developments focus on optimizing sharding protocols and other layer-2 solutions to achieve significant increases in transaction capacity without compromising decentralization or security.