Chainstack vs QuickNode: Dedicated Node Pricing

Flat-rate, usage-based tiers: Pay a fixed monthly fee per node with clear resource caps (e.g., requests/day, archive data). No surprise bandwidth overages. This matters for budget-conscious teams who need predictable OpEx and want to avoid variable cloud provider bills.

Infrastructure agnostic: Deploy nodes across AWS, Google Cloud, and Azure from a single dashboard. Enables global low-latency deployments and avoids vendor lock-in. This is critical for enterprise applications requiring high availability and specific compliance (e.g., data sovereignty).

Modular pricing: Base dedicated node + à la carte features (e.g., Turbo Geth, Trace & Debug, Archive Data). Optimizes cost for specialized needs. This matters for high-performance dApps (like DeFi arbitrage bots) that require specific optimizations but not a full enterprise bundle.

Guanteed response times & dedicated engineers: Higher-tier plans include SLA-backed support (e.g., <15 min response for critical issues). This is non-negotiable for institutional clients and protocols where node downtime directly translates to financial loss or user attrition.

Fixed monthly cost per chain: No surprise usage-based fees. This matters for enterprise budgeting where forecasting OpEx is critical. For example, a dedicated Ethereum node is a flat $399/month, regardless of request volume.

Bundled discounts for multiple nodes: Running nodes for Ethereum, Polygon, and Arbitrum together is more economical than sourcing separately. This matters for protocols operating across multiple L2s who need reliable, co-located infrastructure.

Scalable plans based on requests/second: From Growth (25M reqs/month) to Enterprise (custom). This matters for applications with variable or spiky traffic (e.g., NFT mints, token launches) who can scale cost with demand.

Higher-tier plans include dedicated Slack support and advanced analytics. This matters for teams requiring white-glove service and deep insights into node performance and RPC usage patterns.

Fixed resources on dedicated plans: High-traffic bursts may require a plan upgrade. This is a trade-off for teams that prefer high, unpredictable volume (e.g., major DeFi protocols during market volatility) over cost predictability.

Usage-based billing can lead to variable invoices. Exceeding included requests incurs overage fees. This matters for startups with tight burn rates who need absolute cost certainty each month.

Predictable, flat-rate pricing: No surprise bandwidth overages. Dedicated nodes start at a clear monthly rate, making budget forecasting straightforward for high-throughput protocols like Aave or Uniswap V3. This matters for teams with predictable, high-volume workloads who need to control infrastructure costs.

Infrastructure agnostic deployment: Nodes can be deployed across AWS, Google Cloud, and Azure from a single dashboard. This provides built-in redundancy and avoids vendor lock-in. Critical for enterprise applications requiring 99.9%+ SLA and disaster recovery plans.

Largest supported network portfolio: Access to 30+ chains including Solana, Sui, Aptos, and Cosmos appchains. This matters for protocols like Jupiter Exchange or cross-chain bridges (e.g., Wormhole) that need a single provider for heterogeneous environments.

Guanteed sub-second latency and 24/7 dedicated support: SLA-backed performance with direct engineer access. This is critical for trading desks, NFT marketplaces like OpenSea, and real-time DeFi applications where milliseconds and immediate issue resolution impact revenue.

Slower rollout of new chain support: While core chains (Ethereum, Polygon, Arbitrum) are robust, newer L1/L2 networks may be added after market leaders. This is a trade-off for teams building on emerging ecosystems like Monad or Berachain who need day-one access.

Usage-based add-ons for advanced features: Core dedicated node pricing can escalate with add-ons for enhanced APIs, archival data, or higher request quotas. This requires careful monitoring for applications with spiky or unpredictable traffic patterns.