Indexing Co vs SubQuery
SubQuery offers an SDK for custom indexing projects across 300+ networks, including strong non-EVM and Polkadot support. Indexing Co is a managed pipeline that delivers data directly to your own database with no infrastructure to run.
Your team needs token transfer data across six chains: three EVM, one Substrate-based, one Cosmos chain. You find SubQuery, which genuinely supports all of them. You clone the starter, wire up the manifest, write the mapping functions in TypeScript, and deploy to SubQuery's decentralized network. Now you're managing indexer operators, dealing with SQT token mechanics to pay for queries, and building a GraphQL client to consume the output. Three weeks later, the data is flowing. It's also locked behind a GraphQL API in a format your analytics team can't directly query.
That gap between broad chain coverage and getting data into your actual infrastructure, is where the two products diverge.
Architecture
SubQuery is an SDK for building custom indexing projects. You define a manifest that specifies the chain, data sources, and handler functions. Your mapping functions transform raw events into entities, and SubQuery's runtime indexes those entities into a queryable store. The output is served as a GraphQL API.
Projects run on SubQuery's decentralized network of indexers: independent operators who run your indexing project and earn SQT tokens for doing so. Enterprise customers use managed hosting, but the broader network model assumes token-based consumer/operator economics. SubQuery also runs sharded data nodes for RPC access and is expanding into AI with AskSubQuery for natural language blockchain queries.
The 300+ network coverage is genuine and meaningful, particularly for non-EVM chains like Polkadot, Kusama, and Substrate-based networks where SubQuery has been the default tooling for years.
Indexing Co doesn't ask you to build or deploy an indexer. You define what you want indexed: chains, contracts, events, add optional TypeScript transforms to reshape the data, and choose a destination: PostgreSQL, BigQuery, or a webhook endpoint. The pipeline runs managed. Your data appears in your own database.
There's no GraphQL API sitting between you and your data. No operators to manage. No token balance to maintain. The pipeline processes over 1 billion events per day at sub-500ms block-to-storage on dedicated infrastructure.
Feature Comparison
| Feature | SubQuery | Indexing Co |
|---|---|---|
| Architecture | Indexer SDK + decentralized network | Managed pipeline service |
| Chain support | 300+ networks (broadest in category) | 100+ chains |
| Non-EVM / Polkadot | Strong (original Polkadot indexer) | Supported but narrower non-EVM coverage |
| Data destination | GraphQL API | Your PostgreSQL, BigQuery, or webhook |
| Custom transforms | TypeScript mapping functions | TypeScript transforms |
| Infrastructure to run | Yes, deploy and manage your indexer | None, fully managed |
| Block-to-database delivery | Depends on network operator | sub-500ms (dedicated infra) |
| Payment model | SQT token (or managed tier) | Fiat subscription |
| Enterprise billing | Managed tier available | Yes, standard fiat |
| Output format | GraphQL only | Raw data in your schema |
| Schema ownership | Entities defined in your project | Delivered to your own DB tables |
| Data volume processed | Not published | 1B+ events/day |
When to Use Each
- Your stack includes Polkadot, Kusama, or other Substrate-based chains where SubQuery has the deepest support
- You need the broadest possible multi-chain coverage and some of those chains aren't on other services
- Your team is comfortable deploying and operating an indexer, or you're using SubQuery's managed hosting
- GraphQL output fits your query patterns
- You want an open, community-driven protocol rather than a SaaS service
- You want data delivered directly to your PostgreSQL database or BigQuery, no GraphQL layer
- You need a fully managed pipeline with no indexing infrastructure to operate
- Token mechanics or decentralized operator dependencies would create friction in your stack
- You need predictable latency SLAs and enterprise billing without token exposure
- Your chain footprint is within 100+ chains and you want a simpler operational model