Dedicated vs Shared RPC: Choosing for Production Workloads

Compare shared and dedicated blockchain RPC by workload isolation, operational control, historical data, support, and total cost.

Dedicated vs shared RPC: the practical difference

A shared RPC service distributes infrastructure across multiple customers. A dedicated RPC service reserves some or all node capacity for one customer or workload. The dedicated model can provide better isolation and more configuration control, but it does not automatically make an endpoint faster, more available, or free of limits.

The correct choice depends on the application's traffic, methods, data requirements, and operational risk. A low-volume production application may run well on shared RPC. A busy indexer may need dedicated archive capacity even if its public request rate appears modest.

How shared RPC works

Shared RPC is usually the quickest way to connect an application to a blockchain without operating nodes. The provider manages the underlying clients, upgrades, routing, and common service controls. Customers use a standard endpoint and plan with documented method coverage and capacity policies.

Shared infrastructure fits many development environments, internal tools, wallets, and applications with moderate or variable traffic. It can also provide useful diversity as a secondary endpoint.

The tradeoff is that the service model is standardized. Rate limits, fair-use rules, enabled methods, payload limits, WebSocket behavior, data history, and support levels may not match every production workload. Capacity can also be affected by traffic from other customers, depending on the provider's architecture.

How dedicated RPC works

Dedicated RPC gives a project an isolated endpoint backed by reserved infrastructure. Depending on the service, this may mean a dedicated node, a private cluster, or a routing layer connected to several nodes assigned to the customer.

Teams usually evaluate dedicated blockchain RPC when they need one or more of the following:

  • Sustained or burst traffic that does not fit a shared plan.
  • Private access, IP allowlisting, or environment separation.
  • Specific node clients, versions, interfaces, or method configuration.
  • Archive RPC for indexers, explorers, analytics, or audits.
  • Stable WebSocket subscriptions and closer operational monitoring.
  • Direct coordination for upgrades, incidents, and capacity planning.

The architecture matters more than the word "dedicated." A single reserved node can still fall behind, fail during maintenance, or become saturated by one expensive query pattern. High-availability RPC requires health checks, routing, spare capacity, and a tested failover path.

Compare dedicated and shared RPC by workload

Start with the calls the application actually makes.

For a wallet, examine balance reads, contract calls, gas estimation, transaction submission, and WebSocket use. For an exchange or custodian, include deposit monitoring, confirmation rules, address volume, and recovery after chain reorganizations. For an indexer, measure block-range scans, trace methods, archive-state requests, response sizes, and sustained concurrency.

Record both normal and peak conditions:

  1. Networks, clients, APIs, and exact RPC methods.
  2. Average, peak, and sustained request rates.
  3. Concurrency, payload size, and timeout behavior.
  4. HTTP and WebSocket connection requirements.
  5. Historical block, log, trace, proof, or state requirements.
  6. Latency percentiles and acceptable error rates.
  7. Recovery, support, and incident-communication expectations.

This separates infrastructure problems from application issues. A dedicated endpoint will not fix an unsupported method, an incorrect retry loop, or a request that is inherently expensive for the selected client.

Rate limits and capacity

Shared RPC plans often express capacity through requests per second, request units, credits, or method-specific limits. Those numbers are not directly interchangeable. A lightweight block-number request and a large historical trace can place very different loads on a node.

DTEAM does not impose artificial request-rate limits or usage quotas on dedicated nodes. There is no shared-plan allowance to exhaust. Throughput still depends on the server hardware, storage performance, node client, response sizes, and concurrent queries. No provider-imposed quota does not mean infinite processing capacity.

An indexer can saturate storage with historical queries while making fewer requests per second than a wallet reading recent balances. Size the deployment around those methods and test what happens when concurrency rises: watch queueing, timeouts, and node lag, not just the request counter.

Latency, availability, and failover

Benchmark latency from the application's deployment regions using representative calls. Compare median results as well as p95 and p99 latency, timeouts, and RPC errors. A short test from one laptop says little about production performance.

Availability also depends on the complete path: DNS, routing, load balancing, blockchain-node health, upstream peers, and the chain itself. For critical workloads, evaluate multiple nodes or regions and decide whether the application should use a secondary provider. Test failover before an incident.

Cost and operating responsibility

Shared RPC normally has a lower entry cost and requires less planning. Dedicated infrastructure costs more because capacity is reserved and the deployment may include custom operations or support.

Compare total operating cost, not only the monthly endpoint price. Include engineering time, incident response, node upgrades, archive storage, observability, and the business impact of slow or failed requests. For some workloads, managed dedicated nodes are less expensive than building an internal operations function. For others, shared RPC remains the sensible choice.

Questions to ask an RPC provider

  • Is the backend shared, single-tenant, or a dedicated cluster?
  • Which networks, clients, interfaces, and methods are supported?
  • Is archive data included, and how far back does it go?
  • What capacity, payload, concurrency, and WebSocket policies apply?
  • Which regions are available, and how is traffic routed during a failure?
  • How are node lag, errors, storage, and endpoint health monitored?
  • What maintenance, escalation, support, and service commitments are documented?

If those requirements point to dedicated infrastructure, discuss a dedicated node with DTEAM. Send the target network, RPC methods, peak concurrency, application region, and required history. Networks shown on our site reflect existing operations and relationships, not the limit of what we can deploy: additional networks are available on request, with client and data requirements agreed before deployment. See our dedicated RPC service for the service overview.

Sources and further reading