In the current multi-chain landscape, efficiently and reliably connecting to various EVM chains has become a core challenge for DApp developers. The traditional approach of directly connecting to a single node provider can no longer meet enterprise-grade demands for availability, redundancy, and cost control.

This has given rise to the next generation of RPC infrastructure: intelligent gateways. These are no longer simple endpoint relays but sophisticated proxies equipped with advanced features like load balancing, failover, and caching. Among these, dRPC and eRPC are two representative implementations, yet their design paths and core characteristics are markedly different.

1. Core Feature Comparison: A Schism in Technical Approaches

The following table summarizes the key differences, providing a clear, at-a-glance understanding of their distinct profiles.

Feature Dimension	dRPC (Distributed RPC)	eRPC (EVM RPC Proxy & Cache)
Core Design Philosophy	Building a distributed, high-availability RPC load-balancing network.	Constructing an intelligent caching proxy focused on read optimization and data consistency.
Key Technical Implementation	Multi-provider integration, intelligent routing, failover, load balancing.	Reorg-Aware persistent caching layer, read/write separation.
Performance Focus	High Availability (Uptime), request success rate, latency reduction.	Extreme read performance, drastically reducing calls to underlying nodes, cost optimization.
Data Consistency Model	Eventual consistency (requests are routed to the latest available node).	Strong consistency (cache layer handles reorgs, guaranteeing eventual data correctness).
Primary Advantage	More reliable write operations (`eth_sendTransaction`), higher SLA, ease of use.	Massive read performance gains, significantly lower costs, ideal for indexers, oracles, frontends.
Ideal Use Cases	Exchanges, wallets, general DApps requiring high SLA guarantees.	The Graph indexers, blockchain explorers, on-chain data analysis platforms, DeFi frontends.

2. Technical Deep Dive: Architectural Implementations

dRPC: The Distributed High-Availability Network

dRPC's design philosophy is analogous to a traditional cloud load balancer. Its core value lies in redundancy and failover.

Intelligent Routing & Failover: When you send a request to a dRPC gateway, it is connected to multiple node endpoints from various providers (e.g., Infura, Alchemy, private nodes) behind the scenes. The gateway continuously performs health checks (heartbeat, latency, error rate) on these nodes. If your primary node is unresponsive, the request is seamlessly and automatically rerouted to the healthiest backup node within milliseconds. This is critical for operations like sending transactions (eth_sendRawTransaction) and ensures your application never goes down due to a single point of failure.
Load Balancing: Under high concurrency, dRPC can distribute requests evenly across multiple nodes, preventing any single node from hitting its rate limit, thereby increasing overall throughput.
Simplified Developer Experience: Developers don't need to manually handle complex node-switching logic in their code. By simply configuring a dRPC endpoint, they gain enterprise-grade reliability.

In essence, dRPC ensures your requests are always processed by an available node, with its core goal being to enhance application resilience.

eRPC: The Intelligent Caching Proxy

eRPC's design philosophy is more radical, directly addressing the biggest performance bottleneck in Ethereum RPC calls: repetitive data reads. Its core value is caching and optimization.

Reorg-Aware Persistent Caching: This is eRPC's most crucial technical innovation. A standard cache can return stale or incorrect data during a chain reorganization (reorg). eRPC's caching layer is tightly integrated with the blockchain state, allowing it to detect reorganization events and automatically invalidate stale cache entries, ensuring the data returned is always consistent and correct. This allows it to safely cache nearly any query, including eth_getBalance, eth_call, and even complex eth_getLogs requests.
Extreme Performance & Cost Reduction: Once data is cached, subsequent identical requests are returned directly from memory or disk at microsecond speed and consume zero API credits from the underlying node provider. For indexers or blockchain explorers that need to scan vast amounts of historical logs, the performance improvement is orders of magnitude, while simultaneously slashing infrastructure costs.
Read/Write Separation: eRPC intelligently forwards write operations (e.g., eth_sendTransaction) directly to backend nodes while directing read operations to its high-performance caching layer, optimizing resource utilization.

In essence, eRPC ensures your read requests are as fast and cheap as possible, with its core goal being the radical optimization of read performance and cost efficiency.

3. The Strategic Choice: A Developer's Guide