Goldsky excels at providing a turnkey, production-ready data pipeline with sub-second latency, because it abstracts away the immense operational complexity of running indexers across multiple chains. For example, its infrastructure supports Solana at over 10,000 TPS and Base during peak Superchain activity, handling event streaming without the engineering team managing node infrastructure, data schema migrations, or cross-chain sync logic.
LABS
Comparisons
Goldsky vs Custom Real-time Indexer: Streaming Infrastructure
A technical comparison for CTOs and architects choosing between a managed service like Goldsky and building a custom real-time indexer with Kafka, ClickHouse, or Flink.
Chainscore © 2026
introduction
THE ANALYSIS
Introduction
Choosing between a managed service and a custom build for real-time blockchain data is a foundational decision that impacts scalability, cost, and team focus.
A Custom Real-time Indexer takes a different approach by offering complete sovereignty over the data model, query logic, and underlying infrastructure. This results in a trade-off: you gain ultimate flexibility to implement complex joins, proprietary transformations, and direct database access (e.g., using PostgreSQL or Apache Pinot), but you assume full responsibility for DevOps, monitoring with tools like Grafana, and ensuring 99.9%+ uptime as chain activity scales.
The key trade-off: If your priority is speed-to-market, reduced operational overhead, and multi-chain support out-of-the-box, choose Goldsky. If you prioritize absolute control over your data schema, require deeply custom on-chain/off-chain data joins, and have a dedicated infrastructure team, choose a custom-built solution.
tldr-summary
Goldsky vs Custom Indexer
TL;DR: Key Differentiators
A data-driven breakdown of managed streaming infrastructure versus a self-built solution. Choose based on your team's resources, latency requirements, and long-term roadmap.
01
Goldsky: Time-to-Market & Maintenance
Managed Infrastructure: Zero DevOps overhead for scaling, monitoring, and data pipeline maintenance. This matters for product teams needing to launch features (like NFT mints or live dashboards) in weeks, not quarters, without hiring specialist engineers.
02
Goldsky: Real-time Performance
Sub-Second Latency: Optimized pipelines for chains like Ethereum, Polygon, and Solana deliver event streams in <500ms. This matters for high-frequency applications like on-chain gaming, live trading feeds, or auction platforms where data staleness loses value.
03
Custom Indexer: Total Control & Cost
Architectural Sovereignty: Full control over data schema, logic (e.g., complex DeFi calculations), and infrastructure (AWS/GCP). This matters for protocols with unique data models (e.g., Lido's staking derivatives, Uniswap v4 hooks) where off-the-shelf solutions are insufficient.
04
Custom Indexer: Long-Term Economics
Predictable, Sunk Costs: After initial build, operational costs scale linearly with infra, avoiding vendor markup. This matters for established projects with high, predictable volume (e.g., a top-10 DEX) where managing a $50K/month data bill in-house can be 30-50% cheaper over 3 years.
STREAMING INFRASTRUCTURE HEAD-TO-HEAD
Feature Comparison: Goldsky vs Custom Real-time Indexer
Direct comparison of managed service versus self-hosted indexer for real-time blockchain data.
| Metric / Feature | Goldsky (Managed Service) | Custom Indexer (Self-Hosted) |
|---|---|---|
Time to Production-Ready | < 1 week | 2-6 months |
Initial Setup Cost | $0 (usage-based) | $50K-$200K+ (dev/ops) |
Real-time Latency | < 1 second | ~500ms (optimized) |
Supported Chains | 30+ (EVM, Solana, etc.) | 1-2 (custom deployment) |
Data Schema Flexibility | High (GraphQL, SQL) | Unlimited (full control) |
Maintenance & DevOps | Fully managed | Full team required |
Cost at 10K TPS | $500-$2K/month | $1K-$5K/month (infra + labor) |
pros-cons-a
PROS AND CONS
Goldsky vs Custom Real-time Indexer: Streaming Infrastructure
Key strengths and trade-offs for building real-time data pipelines. Choose based on your team's resources, latency requirements, and data complexity.
01
Goldsky: Managed Speed
Sub-second latency for event streaming from 20+ chains. This matters for applications like live dashboards, on-chain trading bots, and NFT mint tracking that require immediate data visibility without infrastructure tuning.
02
Goldsky: Developer Velocity
SQL-based subgraphs and declarative pipelines reduce development time from months to days. This matters for startups and product teams (e.g., building a DeFi yield aggregator) that need to iterate quickly without hiring specialized indexing engineers.
03
Custom Indexer: Total Control
Fine-tuned data models and deterministic processing for complex logic (e.g., MEV analysis, custom state machine logic). This matters for protocols like Aave or Compound that require absolute precision and control over their risk and accounting data.
04
Custom Indexer: Cost at Scale
Lower long-term variable costs for high-throughput applications after the initial build. This matters for established protocols with predictable, massive data volumes (e.g., processing 1M+ daily transactions) where managed service fees become prohibitive.
05
Goldsky: Operational Overhead
Vendor lock-in risk and limited low-level optimizations. This matters for teams that need to deeply integrate with proprietary data formats or require guarantees that a third-party service cannot provide.
06
Custom Indexer: Build Burden
High initial cost (6-12 months of senior engineer time) and ongoing maintenance for chain upgrades and bug fixes. This matters for resource-constrained teams where core protocol development is the priority.
pros-cons-b
PROS AND CONS
Goldsky vs Custom Real-time Indexer: Streaming Infrastructure
Key strengths and trade-offs for real-time blockchain data pipelines at a glance.
01
Goldsky: Speed to Market
Managed service deployment in minutes: Pre-built connectors for Ethereum, Solana, and Polygon. This matters for MVP launches and teams needing to validate a data product without upfront engineering investment.
02
Goldsky: Operational Overhead
Zero infrastructure management: Goldsky handles node reliability, schema migrations, and scaling. This matters for lean engineering teams who want to focus on application logic, not data pipeline SRE.
03
Custom Indexer: Total Control & Cost
Long-term cost efficiency at scale: Avoids per-query fees; predictable AWS/GCP bill. This matters for high-volume protocols (e.g., perpetual DEXs, gaming) where data costs can become a significant OPEX.
04
Custom Indexer: Protocol-Specific Optimization
Tailored data models and latency: Build schemas optimized for your exact use case (e.g., NFT rarity scores, MEV bundle tracking). This matters for specialized applications where off-the-shelf schemas are insufficient.
05
Goldsky: Limited Customization
Constrained by platform capabilities: Complex transformations or novel data sources may require workarounds. This matters for research-heavy projects or those needing to index less common chains like Monad or Fuel.
06
Custom Indexer: Development & Maintenance Burden
Significant upfront engineering: Requires expertise in Kafka/Redpanda, database optimization, and chain re-org handling. This matters for teams without dedicated data engineers, risking months of delay and technical debt.
CHOOSE YOUR PRIORITY
Decision Framework: When to Choose Which
Goldsky for Speed & Agility
Verdict: The clear choice for rapid prototyping and time-to-market. Strengths: Goldsky's managed service provides sub-second data latency out of the box via its Firehose integration and streaming GraphQL endpoints. You avoid months of DevOps overhead building a custom indexer for chains like Ethereum, Polygon, or Solana. Its pre-built data models for common patterns (ERC-20 transfers, NFT mints) let you query complex on-chain activity in minutes, not weeks. Ideal for hackathons, MVPs, or teams needing to validate a data-dependent feature quickly.
Custom Indexer for Speed & Agility
Verdict: A significant bottleneck for initial development. Strengths: None for this priority. Building a real-time custom indexer from scratch using frameworks like Subsquid, The Graph (Subgraphs), or Envio requires deep expertise in blockchain RPC nodes, data schema design, and performance optimization. The initial setup and tuning to achieve low-latency, reliable streaming can take a quarter or more of engineering time, delaying your core product.
GOLDSKY VS CUSTOM INDEXER
Total Cost of Ownership (TCO) Deep Dive
A technical breakdown of the long-term financial and operational costs of managed streaming infrastructure versus building and maintaining a custom real-time indexer from scratch.
Goldsky is cheaper for most teams in the first 2-3 years. The initial capital outlay for a custom solution—hiring specialized engineers, provisioning cloud infrastructure, and dedicating months to development—often exceeds $500K. Goldsky's pay-as-you-go model eliminates this upfront cost, making it the clear winner for rapid prototyping and projects with variable scale. However, for protocols with massive, predictable data volumes (e.g., processing 100M+ events/day), a custom solution may achieve a lower marginal cost per query over a 5+ year horizon.
verdict
THE ANALYSIS
Final Verdict and Recommendation
Choosing between a managed service and a custom build hinges on your team's resources and your application's specific real-time demands.
Goldsky excels at delivering production-ready, low-latency data streams with minimal operational overhead. Its managed infrastructure, built on technologies like Apache Flink and Kafka, provides sub-2-second latency for event streaming out-of-the-box. For example, protocols like Uniswap and Aave leverage such services to power dashboards and analytics without dedicating engineers to indexer maintenance, ensuring >99.9% uptime and handling Ethereum's peak TPS of over 100 during NFT mints.
A Custom Real-time Indexer takes a different approach by offering ultimate control and cost predictability for massive, specialized data workloads. This strategy results in a significant trade-off: you gain the ability to tailor data schemas, ingestion logic (using tools like The Graph's Substreams, Pinax, or Envio), and deployment topology, but you assume full responsibility for DevOps, monitoring, and scaling—a commitment that can require a dedicated 2-3 engineer team.
The key trade-off: If your priority is speed-to-market, reliability, and freeing up engineering bandwidth, choose Goldsky or a similar managed service like The Graph's Streaming Fast or Subsquid. If you prioritize absolute data control, long-term cost optimization at scale, or have highly unique indexing logic, choose a Custom Real-time Indexer built with Substreams or a comparable framework.
ENQUIRY
Get In Touch
today.
Our experts will offer a free quote and a 30min call to discuss your project.
NDA Protected
Confidentiality24h Response
Time to ValueDirectly to Engineering Team
No Sales Fluff10+
Protocols Shipped
$20M+
TVL Overall