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Overview

Goldsky is a high-performance data indexing provider for Fluent that makes it easy to extract, transform, and load on-chain data to power both application and analytics use cases. Goldsky offers two primary approaches to indexing and accessing blockchain data: Subgraphs (high-performance subgraphs) and Mirror (real-time data replication pipelines).

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Getting started

To use Goldsky, you’ll need to create an account, install the CLI, and log in.

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Subgraphs

Fluent Subgraphs can be deployed on Goldsky in 2 ways:

  • Via CLI from a local subgraph configuration file. If you are familiar with developing subgraphs already, you'll be familiar with this approach; after defining a subgraph locally (with a subgraph.yaml file, a schema.graphql file, and the necessary mappings to translate raw event data into the entities defined in the schema), you can deploy subgraphs to Goldsky (once the Goldsky CLI is installed) using goldsky subgraph deploy <name>/<version> --path . For more, read the step-by-step guide.
  • Via instant subgraphs, where you can pass through a contract address and the ABI for that contract. This is a quick-start option that automatically generates the underlying subgraph configuration files on your behalf, making it easy to extract blockchain event data and serve it as an API endpoint without complex setup. Use the --from-abi flag in the command above instead of --path. For more, read the no-code subgraphs guide.

Fluent’s Devnet is currently available at the chain slug fluent-public-devnet.

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Mirror

Mirror pipelines allow users to replicate data into their own infrastructure (any of the supported sinks) in real time, including both subgraphs as well as chain-level datasets (ie. blocks, logs, transactions, traces). Pipelines can be deployed on Goldsky in 3 ways:

  • Using Goldsky Flow on the dashboard, see walkthrough video here
  • Using the interactive CLI, by entering the command goldsky pipeline create <pipeline-name>. This will kick off a guided flow with the first step to choose the dataset type (project subgraph, community subgraph, or chain-level dataset). You'll then be guided through adding some simple filters to this data and where to persist the results.
  • Using a definition file, by entering the command goldsky pipeline create <pipeline-name> --definition-path <path-to-file>. This makes it easier to set up complex pipelines involving multiple sources, multiple sinks, and more complex, SQL-based transformations. For the full reference documentation on, click here.

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Getting support

Can't find what you're looking for? Reach out to us at support@goldsky.com for help.