Public Subgraphs excel at community-driven development and network effects because they are deployed to The Graph's decentralized network. For example, a public subgraph like Uniswap's, which processes over 1 million queries daily, benefits from shared indexing resources and becomes a public good that any dApp (like DeFi dashboards or portfolio trackers) can query via the GraphQL endpoint, fostering composability across the ecosystem.
LABS
Comparisons
Public vs Private Subgraphs: A Technical Comparison for Protocol Architects
An unbiased analysis comparing publicly queryable subgraphs on The Graph Network against privately deployed subgraphs. We evaluate cost, security, performance, and governance to help CTOs and technical leads make the optimal deployment decision for their protocol's data.
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introduction
THE ANALYSIS
Introduction: The Core Trade-off Between Openness and Control
Choosing a subgraph deployment model is a foundational decision that determines your data's accessibility, security, and operational overhead.
Private Subgraphs take a different approach by running on a dedicated, permissioned infrastructure like The Graph's Subgraph Studio or a self-hosted Graph Node. This results in a trade-off: you gain full control over indexing rules, upgrade schedules, and data privacy—critical for pre-launch protocols or handling sensitive financial data—but you assume the operational burden and cost of maintaining the indexer service.
The key trade-off: If your priority is maximizing developer adoption, reducing operational overhead, and leveraging decentralized infrastructure, choose a Public Subgraph. If you prioritize data confidentiality, deterministic performance SLAs, and custom indexing logic for a proprietary application, choose a Private Subgraph.
tldr-summary
Public vs Private Subgraphs
TL;DR: Key Differentiators at a Glance
A quick comparison of the core trade-offs between publicly hosted and privately deployed subgraphs on The Graph Network.
01
Public Subgraph: Pros
Decentralized & Censorship-Resistant: Indexed data is served by a network of independent Indexers, ensuring high availability and no single point of failure. This matters for dApps requiring maximum uptime and neutrality, like DeFi frontends (Uniswap) or public analytics dashboards.
Zero Infrastructure Overhead: No need to manage Graph Node servers, databases, or indexing pipelines. The Graph Network handles scaling and maintenance. This matters for teams with limited DevOps resources who want to focus on application logic.
02
Public Subgraph: Cons
Query Cost & Complexity: Requires purchasing and managing GRT tokens for query fees, adding financial and operational overhead. This matters for high-traffic applications where query costs can become significant.
Limited Control & Privacy: Subgraph code, schema, and indexed data are fully public. This matters for enterprise applications or pre-launch protocols that need to keep logic or data confidential.
03
Private Subgraph: Pros
Full Control & Customization: Complete ownership over the Graph Node, database, and indexing logic. Enables custom optimizations, specific blockchain RPC nodes, and direct database access. This matters for protocols with complex data transformations or specific performance SLAs.
Data Privacy & Cost Predictability: All data stays within your infrastructure. Query costs are fixed (hosting fees) versus variable (GRT payments). This matters for handling sensitive user data or applications with strict, predictable budgeting.
04
Private Subgraph: Cons
Operational Burden: Requires provisioning, monitoring, and scaling your own Graph Node infrastructure (e.g., on AWS, GCP). This matters for teams without dedicated SRE/DevOps capacity.
Centralized Risk: Your application's data availability depends on the uptime of your self-hosted node. This matters for mission-critical dApps where self-hosted downtime directly impacts users.
HEAD-TO-HEAD COMPARISON
Head-to-Head Feature Comparison: Public vs Private Subgraphs
Direct comparison of deployment models for The Graph's indexing layer.
| Metric / Feature | Public Subgraph | Private Subgraph |
|---|---|---|
Deployment & Hosting | The Graph Network (Decentralized) | Self-hosted or Subgraph Studio |
Indexer Curation | Required (GRT Bonding) | Not Required |
Query Cost | GRT Payment per Query | $0 (Infrastructure Cost Only) |
Data Privacy | ||
Custom Chain Support | Approved Networks Only | Any EVM Chain (e.g., Arbitrum, Base) |
Uptime SLA | Variable (Decentralized Network) | Controlled by Developer |
Best For | Public DApp Data | Proprietary Data, Enterprise |
pros-cons-a
A Balanced Technical Comparison
Public Subgraphs: Pros and Cons
Choosing between a public and private Subgraph deployment is a foundational infrastructure decision. This comparison highlights the key trade-offs in cost, control, and performance to guide your architecture.
01
Public Subgraph: Key Pro
Zero-cost indexing & hosting: The Graph's decentralized network indexes and serves the data. This eliminates the operational overhead and server costs (e.g., AWS RDS, managed Postgres) for teams, ideal for bootstrapped projects or public goods like Uniswap or Compound.
02
Public Subgraph: Key Con
No query performance SLAs: You rely on The Graph's decentralized network's uptime and speed. During peak loads or network congestion, query latency can spike unpredictably. Not suitable for applications requiring guaranteed sub-100ms p99 latency for critical user actions.
03
Private Subgraph: Key Pro
Full control over performance & schema: Host the indexer and database (Postgres) in your own cloud (AWS, GCP). Enables custom optimizations, real-time migrations, and integration with internal BI tools (e.g., Grafana, Metabase). Essential for high-frequency dApps like perpetuals exchanges (e.g., dYdX v3) or analytics dashboards.
04
Private Subgraph: Key Con
Significant operational overhead: Requires managing infrastructure, monitoring, database scaling, and ensuring indexer sync reliability. This introduces DevOps costs and complexity, demanding dedicated engineering resources that could be spent on core protocol development.
pros-cons-b
PUBLIC VS. PRIVATE DEPLOYMENT
Private Subgraphs: Pros and Cons
Choosing between a public or private Subgraph deployment is a foundational architectural decision. This comparison highlights the key trade-offs in security, control, performance, and cost.
01
Public Subgraph: Pros
Rapid Development & Community: Deploy to The Graph's decentralized network in minutes. Leverage the hosted service's infrastructure with zero operational overhead. Ideal for open-source dApps like Uniswap or Aave that benefit from community indexing and verification.
Zero Infrastructure Cost: No direct cost for indexing or querying. Query fees are abstracted for end-users via the gateway. Perfect for bootstrapped projects or public data that doesn't require access control.
02
Public Subgraph: Cons
No Access Control: Data is openly queryable by anyone via the public GraphQL endpoint. Unsuitable for indexing private on-chain data (e.g., NFT metadata for an unreleased collection) or proprietary trading logic.
Limited Performance Guarantees: Shares resources on a public network. Query speeds and uptime depend on decentralized indexer performance, which can vary. Not ideal for applications requiring consistent sub-100ms p95 latency.
03
Private Subgraph: Pros
Complete Data Control & Security: Deploy to a dedicated node (e.g., using Subgraph Studio with a private gateway or a self-hosted Graph Node). Enforce API keys, rate limits, and IP whitelisting. Essential for enterprises, financial protocols like Goldfinch, or any app handling sensitive on-chain data.
Deterministic Performance & Uptime: Control your infrastructure stack (AWS, GCP). Use tools like Grafana and Prometheus for monitoring. Achieve SLA-backed performance (>99.9% uptime, <50ms queries) critical for high-frequency dashboards or order-book systems.
04
Private Subgraph: Cons
Significant Operational Overhead: You are responsible for provisioning, scaling, and maintaining the Graph Node, Postgres database, and IPFS instance. Requires dedicated DevOps resources or managed services like Chainscore.
Direct Infrastructure Costs: Incur cloud provider costs (compute, storage, egress). At scale, this can range from $500 to $5,000+ monthly, compared to the $0 base cost of the public hosted service.
CHOOSE YOUR PRIORITY
Decision Framework: When to Choose Which
Public Subgraphs for Protocol Teams
Verdict: The default for most decentralized applications. Strengths: Public subgraphs are essential for composability and user-facing analytics. They allow any frontend (like Uniswap's interface), wallet (like Rainbow), or aggregator (like 1inch) to query your protocol's indexed data without permission. This drives adoption and integration. They are hosted on The Graph's decentralized network, ensuring censorship resistance and aligning with Web3 ethos. Trade-offs: Indexing speed and uptime depend on the network's Indexers. You relinquish direct operational control. Key Metrics: Query fees are paid in GRT, and performance is tied to the subgraph's curation signal.
Private Subgraphs for Protocol Teams
Verdict: Critical for internal operations and sensitive data. Strengths: A private subgraph, deployed to a service like The Graph Studio or a self-hosted Graph Node, gives you full control over the indexing infrastructure. This is mandatory for indexing pre-launch contracts, processing proprietary trading signals, or handling data not meant for public consumption (e.g., user-specific off-chain data merged with on-chain events). Trade-offs: You bear the full infrastructure cost and maintenance burden. It breaks permissionless composability.
SUBGRAPH DEPLOYMENT
Technical Deep Dive: Architecture and Implementation
Choosing between public and private subgraphs is a foundational architectural decision for your dApp's data layer. This section breaks down the key technical trade-offs in performance, cost, security, and maintenance.
The core difference is access control and hosting. A public subgraph is deployed to The Graph's decentralized network (e.g., using the Graph Explorer), where its data is indexed and served by a permissionless set of Indexers. A private subgraph is hosted on a dedicated service, such as The Graph Studio or a self-hosted Graph Node, where you control who can query the API endpoint and manage the underlying infrastructure.
verdict
THE ANALYSIS
Final Verdict and Strategic Recommendation
Choosing between public and private subgraphs is a strategic decision balancing decentralization, control, and cost.
Public Subgraphs excel at fostering ecosystem growth and composability because they are open, verifiable, and discoverable on The Graph's decentralized network. For example, a protocol like Uniswap relies on its public subgraph, which serves over 1.2 million daily queries, enabling seamless integration for hundreds of dApps, wallets, and analytics dashboards without any single point of failure. This model leverages the security and liveness of the decentralized network, with indexing rewards paid in GRT tokens.
Private Subgraphs take a different approach by offering dedicated, controlled infrastructure. This results in a trade-off: you gain predictable performance, custom indexing logic, and data privacy—critical for pre-launch protocols or proprietary analytics—but sacrifice the network effects of public discovery. You operate and pay for your own indexer(s) or use a hosted service like The Graph Studio, which can cost thousands of dollars monthly but guarantees sub-second query latency and exclusive access.
The key trade-off: If your priority is maximizing developer adoption, trustlessness, and ecosystem integration, choose a Public Subgraph. If you prioritize data privacy, bespoke logic, and guaranteed performance SLAs for internal or gated applications, choose a Private Subgraph. For many protocols, the optimal strategy is a hybrid: launching with a private subgraph for controlled development and migrating key data feeds to a public subgraph at mainnet launch to unlock the full power of Web3 composability.
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